1

Dr Constantinos Ikonomou

Ph.D. University of Cambridge

Department of Economics

University of Athens,

Law School

RSA Early Career Grant and University of Athens

Directing Growth in Europe

2

Directing Growth in Europe

Extended abstract

Europe needs to strengthen its economic integration. The EU has emphasized the creation

and progressive integration of European states through capital and labour accumulation,

infrastructure development, endogenous growth, free trade, monetary unification,

institutional creation and change, competitiveness, entrepreneurship, business and SME

support and sustainable development. Substantial efforts were taken and funds were

devoted to related policies, especially from EU member-states, which have enhanced

capital and labour mobility in Europe and contributed in setting-up long-term growth

conditions.

The present study uses a broad range of variables for 34 states from geographical Europe

in the 2000-2008 period. It assesses their correlation with distance from Brussels, growth

rates and growth levels (constant prices). Differences in the Pearson correlation

coefficients from an initial to a final year are also calculated, indicating change and

convergence among states. The results show that the EU has strengthened its overall

position over the study period. Imbalances between peripheral and central states and a

very clear pattern in growth gaps between advanced and non-advanced states have

appeared. Policies have assisted centrally located and advanced European states, which

sustain their competitive position via trade, export of goods and strengthening of capital

formation. Although growth rates were higher in peripheral and less advanced countries,

their position is weakened, in numerous correlations tested. The prospect of a dualism in

the European economy and that of a two-sector non-integrated economy is likely to be

created.

It appears that, despite initial expectations, the actual dimension and extent of centrifugal

forces in operation were not realised, and theories from regional studies and economic

geography, if seen from a broader, pan-European geographical perspective, were not

taken sufficiently into account, such as: Myrdal, 1957; Hoover, 1948; Losch, 1954;

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Christaller, 1966, Perroux, 1955 and others. Due to the opening of borders, the peripheral

and less advanced states experience strong competitive pressure that causes

unemployment, and the operation of detrimental forces against their economic, social,

and political wellbeing. Other forces increase immigration. Implications should also be

seen in relation to the relaxing of social, ethical or cultural values that maintained the

integrity of national characteristics, to continuous social imbalances and change, the

diffusion of social pathologies such as corruption, through the operation of networks -

since people are connected and learn from each other (Christakis and Fowler, 2009)- as

well as the rise of collective violence (de la Roche, 1996). Despite that, peripheral and

less advanced states are considered to be responsible for many of the economic and social

problems, perpetuated in their territories.

On the other hand side, existing policies have managed to create so far those backward

and forward linkages needed in the European economy and a chain of disequilibria

necessary to produce and sustain growth, especially in the most advanced states

(Hirschman, 1958). While doing so, they have also laid down additional, necessary

foundations on the historical ones, bringing European states closer to each other, in what

appeared once to be a very dissimilar European geography. A long distance is eliminated

between what separated once national populations in Europe and what unites them now.

Peripheral states need now to enter a new, take-off stage of development (Rostow, 1960),

by increasing their clustering around the most advanced economies. This stage of

economic integration will require a “big push” in their economy (Rosestein-Rodan,

1943), especially through investments in hybrid industrial and manufacturing products of

high value added (Dixit & Stiglitz, 1977), such as helicopters. Such investments should

be followed by the consequent creation of several millions of jobs, especially in SMEs

(Hirschman, 1958), favouring, at the same time, the transformation of production in

European centres (Combes et al, 2008). The EU could strategically support such infant

European industries. Such an investment push is justified by macroeconomic analysis.

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The EU needs to operate towards a seemingly opposite direction from the present,

emphasizing the association among its economies and the process of uniting its common

European interests. Emphasis should be given on the “cement” rather than the “stones” of

the European edifice, by pursuing competitiveness alone. Rather the target should now be

to turn Europe into a new stage of integration, emphasizing the elements for creation of a

European-wide cluster, as extensively discussed in cluster theory (see in Crux and

Texeira, 2010 or Martin and Sunley, 2003) that will enhance growth opportunities, offer

economic freedom and will be characterised less by harsh competition and more by

economic “amyllae”1.

1. The theoretical framework for building Europe

The united Europe is not only the European Union but its outcome. The unification

process may comprise Russia in the family of EU states one day, which could create

complications, if problems in every different situation during the unification process are

not acknowledged in time. The key challenge throughout the unification process is how

to agree and implement changes both inside the EU and at the European level, without

hiding the truth about the present situation at the EU, the problems and challenges it

faces, the deceptions it creates or the negative forces denying its operation. It is better not

to assume different, fallacious views on where the EU actually stands, in order to reach a

better future for the benefit of its citizens and the generations to come, all over Europe.

This knowledge is ecumenical and does not belong only to the EU, as similar unification

efforts are in train all around the world. Besides, it is likely that many contemporary EU

problems relate to the application of economic theory or to theory itself. Europe has

1 The Greek noun άμιλλα is one of the ancient Greek words difficult to translate in the English vocabulary.

There is no exact synonym. A possible writing, offering a pronunciation close to the Greek, could be the

following: “amyllae”. According to Babiniotes, (1998) its root (άμα) might come from an ancient Greek

root meaning “together” and “simultaneously”. It is understood as the competition without rivalry that

intends to help participants to improve themselves in their efforts to excel (Babiniotes, 1998). The word has

a positive connotation, usually explained in Greek by reference to the Olympic Games as “noble

competition” that emphasizes an environment of collaboration and co-operation. Such an environment

prevailed every time the Olympic Games were held. City-states and well-known personalities and athletes

across the Greek territory used to gather to celebrate a common purpose, the organisation of the Olympic

Games, in a period of Olympic truce.

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already achieved a lot in bringing states together, shifting from a point in history

characterised by a very wide heterogeneity among EU states to the present.

The creation of the EU is largely based on economic, social, political, cultural and other

foundations that pre-existed in nation-states. The EU sought to enlarge them, by creating

a new basis, using, to a large extent, economic theory and its applications.

Based on the neoclassical growth model (Solow, 1956; Swan, 1963), conditions for

capital accumulation across the European space were and are still sought, where needed.

The use of the model for tracing convergence among states has offered limited such

evidence (Barro and Sala-i-Martin, 1992; Casseli et al., 1996; McQuinn and Whelan,

2006). Perfect mobility for both European capital and labour, as assumed in the

neoclassical model, was sought by the use of core infrastructure (Aschauer, 1989;

Reinikka and Svensson, 2002). In earlier, premature integration stages, the EU was

suffering from very low factor mobility among states. Large-scale infrastructure

developments would enhance mobility at the European level, but not necessarily support

national capital and labour mobility, largely depending on their competitiveness.

Infrastructure alone could also bring negative effects, e.g. by increasing costs. Hence

public spending had to increasingly engage with private sector needs to reduce these

effects (Aschauer, 1988; Otto and Voss, 1998).

Since the 1980’s, the advent of endogenous and new growth theory emphasized human

capital, knowledge, learning-by-doing, R&D, technology and specialisation,

reformulating previous debates in economic theory (as in Lewis, 1965; Schumpeter, 1942

or others). Related policies were thought necessary for achieving convergence and

integration (Thirlwall, 2003; Barro, 1991; Batiz and Romer, 1991; Romer, 1986; Aghion

and Howitt, 2009), even though such views neglected the importance of market sizes,

core-periphery imbalances and the need for institutional and social changes (Thirlwall,

2003; Aghion and Howitt, 2009; Martin and Sunley, 1998).

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Progressively, various thoughts on the creation of a common currency gained ground in

EU policy circles. The EU monetary unification came as an additional attempt in the

history of nations to create larger geographical areas of stable economic environments,

based, this time, on more solidly built monetary and optimum currency area theory.

Derived from an effort to understand crises in the balance of payment and substantial

disequilibria in international systems, the optimum currency area theory (OCA)

recommended that nations can share a single currency, under certain conditions

(Mundell, 1961). The initial targets set for the development of such a theory were full

employment, balanced international payments and an average, stable price level

(McKinnon, 1963). Monetary unification was expected to eliminate transaction costs, to

provide a better performance for money as a medium for exchange and a unit of account

(Ricci, 1997, Mundell, 1961) and to create efficiency gains from eliminating relative

price distortions generated by transaction costs. Small countries attaching to larger

currency areas were suggested to share potential benefits (Alesina and Barro, 2002). A

single currency was believed to speed-up the integration process, and to be useful with

regard to business cycles, the increase of trade and the reduction of exchange rate

volatility (Rose and Engel, 2002). The absence of exchange rates would deprive

economies from a short-run adjustment mechanism needed to avoid asymmetric shocks,

price rises due to shocks and vulnerability to international financial crises (Ricci, 1997).

Monetary theory had failed to acknowledge price differentiation in very large common

geographical spaces, as suggested in spatial discrimination and spatial pricing theory

(Hotelling, 1929; Hoover, 1934 and others) or price rises resulting from the unification of

demand and supply in the EU, the operation of a Balassa-Samuelson effect, mainly in

economies based on trade (Balassa, 1964; Samuelson, 1964), or even to take into account

the effects of state-level policies.

Various views on trade, exports and trade openness helped to realise the benefits of trade

openness and expansion inside the EU. Trade would enhance capital and labour mobility,

promote competition, technology transfer and knowledge diffusion, achieve state

democratisation especially in less democratic societies and bring new perceptions,

principles and techniques in the production of peripheral and less advanced states.

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Exports both at the state and regional-level could bring growth (North, 1955; Tiebout,

1956). In the classic view, held by Ricardo and Mill, trade would offer a comparative -

rather than just absolute- advantage to states. In the assumption that trade is a positive

sum game and regional economies are led to a mutually beneficial specialisation path,

which regulates international and global wealth and production. According to the

Heckscher and Ohlin view, such comparative advantage relates to the relative abundance

of production factors and their intensive use, hence international trade would be shaped

by resource differences among EU and European nations and their allocation. From this

perspective, states with more intensive use of global transport networks for their

products, with international transport infrastructure and vehicles of low transportation

costs for their products, produced even outside their borders and with low labour costs,

would benefit mostly. Leontief’s research (known as the Leontief paradox) proved that

Heckscher and Ohlin’s views were controversial and that more analysis was needed on

the complexity of factors affecting trade, such as human resources, labour or interest

groups (as in Krugman and Obstfeld, 2000; Grossman and Helpman, 2002; 1990). Trade

and its composition could alter relative prices, the supply and demand of goods, while the

composition of production by sector could determine growth rates, when different goods

have different technological progress rates (Spilimbergo, 2000). By taking into account

imperfect competition, new trade theory brought various novelties, highlighting the need

for strategic trade and selective use of trade instruments, such as infant industry

protection (Krugman, 1995; Grossman, 1992; Krugman and Obstfeld, 2000).

Dumping could reveal the benefits of price competition for larger firms (Krugman and

Obstfeld, 2000). Disassociated from their national shell, trade interests would retreat from

their historical role to protect peripheral production, seeking to gain advantages against

peripheral (or any other) production. Local and regional production would be

progressively replaced by trade, various concerns on product quality removed and the

peripheral and less advanced areas left in a more vulnerable position, with insufficient

production levels, less recognisable brand names and reduced product quality. In the

absence of a range of policy incentives to promote mergers in peripheries, transportation

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cost reductions2 and the creation of larger firms to enhance economies of scale, peripheral

production had to offer substantial profit chances and significant varieties or else risked

disappearing. The picture of a Europe driven by trade appears to emerge (Tsoukalis,

2005).

Due to the opening of borders and the release of agglomeration forces, a “new

competition” had to be created, through institutions of industrial restructuring and

specific regulatory authorities (Best, 1991). The theory of competitiveness emphasized a

combination of microeconomic and macroeconomic growth factors, the role of

competition, endogenous growth factors, basic points made in the theory of growth, the

role of demand and supply, of manufacturing and businesses (e.g. in Porter, 1998).

Development in competitiveness theory coincided historically with the need to enhance

competition, especially in less advanced European states coming from a central planning

background. Initially developed for single nations, it was transferred at the regional and

local level (Budd and Hirmis, 2004; Boschma, 2004, Turok, 2004), also followed by a

criticism on its relative significance or even elusiveness (Kitson et al., 2004; Bristow,

2009). Though competitiveness was promoted as a national or regional target, the pan-

European maximisation of value-added was not crystallised as an explicit EU target.

Along with competitiveness theory, the development of entrepreneurship, entrepreneurial

dynamism, and policies to support new, small and medium sized enterprises was thought

necessary, given the work of Schumpeter (1942) and other economists.

Regional economic association and the diffusion of associative practices across the

European space were discussed to contribute to collective learning and improve

production, bringing innovation and growth (Cooke and Morgan, 1999). In various

readings knowledge, science, research and their diffusion were considered a precondition

for national and regional growth across Europe. The emergence of an information society

would promote their growth and diffusion, via information and communication

technologies (Antonelli, 2002; Dimelis and Papaioannou, 2003). Long-term arrangements

2 As in the case of agricultural products that re-gain in several circumstances advantages lost from distance

to centres through the Common Agricultural Policy.

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were needed to set-up necessary institutions of knowledge, such as libraries, universities,

research centres, technological or other educational institutions. Such institutions would

help, in conjunction with the progressive building of the information society, to organise

human capital resources, innovation activity, the promotion of know-what, know-why,

know-who or other learning processes, sheltering different kinds and degrees of

knowledge, tacit or codified, formal or not (Gregersen and Johnson, 1996).

The more general role played by institutions in building the EU and a spirit of European

solidarity was highlighted since the very early steps of European integration. Their role in

growth was referred to in various discourses in economic theory, such as the Regulation

School, the “national business systems”, “national innovation systems” and the “varieties

of capitalism” discourses (see in North, 1990; Gertler, 2010; Martin and Sunley, 2003).

Institutional creation, renewal or development is indispensable for bringing a union of

states together. Institutions help to resolve problems and conflicts among interests,

explore and economise resources, guide actor’s behaviour, set up strategic agendas,

provide information, reduce opportunism and create stable expectations, by setting the

“rules of the game” (Borzel, 2002), since institutions progressively promote knowledge

and sustain new practices, ideas and values (Rosamond, 2004). Institutional renewal is

needed, since as intermediary variables, they affect economic path dependence, operating

in a regulative manner, which can increase the danger of reduced freedom and rational

choice (Nugent, 2006).

Various international relation theories, such as the federalist, co-federalist, the

functionalism, neo-functionalism or the concessional view and comparative political

economy studies shed more light on the process of integration. No single theory managed

to describe or explain it in full. Regional “players” would integrate through functional co-

operation and interaction, in a progressive, functional spill-over process. Various

consensuses would improve cooperation and the level of authority for common

institutions, enhancing the concentration process of functions (Haas, 1958). Nation-states

would transfer more power to central authorities (Haas, 1972, Earnshaw and Judge,

1996). High give-up costs and the legitimisation of processes under operation would lead

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to integration by way of determinism. Concessions would realistically guide inter-

governmental policy making. For new-institutionalism, institutions would express state

needs. The development of networks would support decision-making, compromise and

governance (Nugent, 2006). Inside the EU, governance is promoted by the classic

Commission method, ministerial meetings, conferences and agreements at the level of

permanent representations, with continuous contacting of partners in a spirit of comprise

and co-operation. New emerging forms of governance, such as the Open Coordination

Method, social dialogue, independent authorities and self-regulation are multi-functional

and characterised by variety, flexibility, decentralisation, collaborative work, a learning

process and a commitment (Manouvelos, 2010). Forging unity within the context of state

variation and difference was necessary, as highlighted by federalism.

An economic union of states is the outcome of different stages of integration, commonly

preceded by a customs union or a common market, which are progressively built, in

different and necessary stages. The full economic integration requires the unification of

economic, monetary, fiscal and other public sector policies. Despite efforts taken, the

direct implementation of economic and fiscal unification remains a difficult experiment,

since it is related to monetary unification and the various levels of growth and living

conditions in the EU member-states.

2. The prospect of divergence: re-examining the theory

In the open-border EU environment of free labour and capital movements, imbalances

would increase due to the operation of stock markets and the influx of speculative capital

in national markets.

The extent of centrifugal forces in operation and their geographical scale was not realised

in full and is much higher than originally thought. Various theories in regional studies

and economic geography were used at an early stage to diagnose the prospect or tendency

of enhancing core-periphery imbalances and the division between wealthy and poor

states. This was highlighted in central place theory (Christaller, 1933; Losch, 1954),

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growth pole theory (Perroux, 1955), studies on the location of economic activity (Hoover,

1948) and the theory of cumulative causation (Myrdal, 1957; Kaldor, 1970) that

highlighted the presence of backwash and spread effects and of a detrimental mechanism

in operation, against some peripheries. Such a prospect is also emphasized in new

economic geography readings, emphasizing the significance of locational factors,

transportation costs, economies of scale and manufacturing production (Krugman, 1991;

Fujita et al., 1999).

Very often investors tend to expend all their energy in growth poles, seeking to take

advantage of the constantly overestimated external economies in them, while ignoring

opportunities in other areas that remain unexplored (Hirschman, 1958). The intensity of

such external economies and agglomeration forces in operation before the opening of EU

borders ought to be expected to multiply after their opening, favouring specific locations

in the EU. The agglomeration of economic forces around central European regions is also

witnessed in the discussions held on the European “triangle”, “backbone”, the “blue

banana”, the “red octopus” or other shapes formed in the wider central European area or

in other views held on the Europe of multiple “speeds”, variable “geometry”,

homocentric circles, and the distinction between the old and the new Europe.

The analysis of multipliers that take into account interregional trade had diagnosed that

within a group of regions without monetary and fiscal policy, the creation of large

regional state deficits is possible, intensifying economic imbalances (Richardson, 1969

and others). Transferred at the state-level, and under the hypothesis of a closed economy

for trade outside the EU, this analysis predicted potentially intense imbalances in trade

deficits for some of the states, and, consequently in their balance of payments, given

state-level differences in competitiveness, institutions, education, the exploitation of

human resources or other factors distinguishing more from less developed economies.

Dualist theories explained the prospect of creation of an economic dualism between the

most and the less developed states (for example between the Northern and Southern EU),

where one segment of the EU state and regional economies would be the most modern, of

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highly developed capitalism, and the other the more traditional and less technologically

advanced (Boeke, 1956). Viewed in the light of the creation of comparative advantage,

sector theory highlighted the prospect of the creation of a unified economy with

specialised sectors, per region, state or group of states. Such an evolution is likely to

perpetuate the gap between wealthier and poorer economies at the expense of the most

vulnerable and peripheral (Emmanuel, 1972), supporting a vicious-circle inside the EU

economy. Following resource-scarcity theory, places in Europe with resource scarcity are

more likely to have limited chances for growth and be incapable of exploiting new

resources, to turn them to new comparative advantages.

3. Social Dimensions of the Diverging process in European Economies

Increasing economic imbalances would naturally bring population movements, not only

nationally but also at the European scale, especially that of highly educated and trained

workforce (Hirschman, 1958). Immigration in Europe has a double hypostasis, derived

from domestic population movements and from outside Europe and the EU. Globalisation

eases migration to Europe, due to intense international demographic pressures, the

development of transport, communication and other infrastructure and the multiplication

of causes pushing foreign populations towards better social and economic conditions in

the EU. The latter include environmental reasons, the search for freedom, human dignity,

the respect of human rights, the offering of political asylum and the advent of refugees

from places of erupting violence (Jandl, 2007; King, 2002; Schmidt, 1999). Immigration

has a multidimensional nature (Goldstein, 1976), and preeminent among the pull factors

are the economic and labour causes, the social and ethnic networking in places of

destination, but also the intensity of centre-periphery relations, in the cultural and system

theory (Hooghe et al., 2008). Large migration influxes first arrive at the EU periphery,

which suffers mostly from its consequences, often including a challenge of domestic

residency, the value of citizenship and a request for “rights and papers” (Poros, 2008).

The development of only few regions, sections or sectors in the economy produces

economic and social gaps between the more progressive parts of the society and those

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remaining backwards or excluded from the production process (Hirschman, 1958). This

gap further impedes growth, since “successful groups or regions proclaim their

superiority over the rest of the country and their countrymen” (Hirschman, 1958; p.185),

by highlighting the qualities differentiating them from other groups or regions and by

creating for the rest a stereotype image of laziness. On the other hand the less developed

groups, regions or sections of a society reply to these superiority claims by accusing the

“nouveaux-riches” “of crass materialism, sharp practices, and disregard for the country’s

traditional cultural and spiritual values” (Hirschman, 1958; p.186). These views apply for

Southern and Eastern EU states, between the more and the less advanced parts of their

societies, as well as between the Northern and Southern parts in Europe.

Together with economic change, the EU populations had to intensively assimilate new

values brought from abroad, compromising with continuous social change. By opening

their borders, populations were asked to adopt new values and to change their

organisation and composition (as discussed in Ginsberg, 1958), always in relation to their

pre-existing structure and organisation. Intensive social changes would bring social

exclusion, especially for those parts of domestic societies left outside the implementation

of changes. Various and intensive economic changes and imbalances, such as those

stemming from rises in prices and costs of living, alter the character of what was once a

stable social environment, with specific and discernible norms, culture, symbols and

values, reducing a sense of social consciousness and pushing towards the expression of

social cohesion problems. In such environments, the spread of various social pathologies

or practices is likely to take place, such as corruption, supported by the operation of

networks, since people are connected and learn from each other in various forms of social

networks (Christakis and Fowler; 2009). Such networks have the power to shape human

conduct and affect the same morale and freedom of choice (Christakis and Fowler; 2009).

Against the intensity of economic and social change and imbalance, phenomena of

collective violence are likely to appear (de la Roche, 1996; The Telegraph, 2010), as an

effort to regain social control lost by groups and parts of the society. Such phenomena are

spread in environments of unemployment, reduced opportunity and underinvestment,

where some part of societies have differential access to strategic resources from other

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“socially distinct entities” and cannot obtain equal treatment by gaining a more

substantial role in the production of strategic resources (that would have offered them a

better integration at the society, as explained by Paynter, 1989). As opposed to such

angles explaining the emphasis on their social problems, societies in peripheral states are

assumed to be fully responsible for their presence and expansion over the last decade.

4. Directing European growth

The aforementioned views make difficult, if not unrealistic, the target of balanced

growth. An opposite view from the balanced growth thesis recommends that in practice

growth is the outcome of a chain of disequilibria and imbalances in the economy

(Hirschman, 1958), according to which “in the geographical sense, growth is necessarily

unbalanced” (Hirschman, 1958, p. 184). Unbalanced growth is compatible with modern

approaches in economic theory, assuming various forms of imperfect rather than perfect

competition to offer higher profit chances for firms and the economy, which however

sustain various inefficiencies. There are however a certain degree of economic

imbalances that a nation or a union of states could sustain. According to Hirschman

(1958), non-balanced growth is combined with the creation of forward and backward

linkages.

These points should be seen in relation to the principal problem for the most developed

states, i.e. their weakness in sustaining high growth rates. By reversing the study of

economic imbalances at the European level by 180 degrees and provisionally accepting

their intensity, we can manage also to accept that such imbalances have allowed growth

to take place inside EU states at a scale that would never have happened otherwise, and

may have never operated as a sustaining force for the common economy. The

development of international trade and the increasing economic cooperation across EU

states allowed the creation of backward and forward linkages -mostly to the benefit of

some EU states-, putting the European economy on a long-term developmental basis.

From this perspective, it is more the target of balancing the already heavily imbalanced

growth in some cases that is currently needed to be achieved as a prospect, rather than

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reducing the operation of pan-European linkages, which nurture and sustain the growth

prospects of the most advanced states. It is for the common European benefit that due to

the creation and operation of such linkages, EU economic and political interests from

more advanced states have embraced the current direction for the European economy and

are now in the position to realise the necessity of a common economic destiny with the

less advanced and peripheral states and wish their better economic integration. Without

substantial benefits for their economies, it is questionable whether advanced states would

have ever reached a position today to consider supporting the progressive creation of a

new stage of economic integration in Europe. The full economic integration in Europe

will take time and face many problems and challenges, due to creation of heavy

imbalances and the role of human and societal choices. However, from the moment that it

is being realised that economic integration in Europe is in its half-way through or at least

at some non-final stage, it can also be realised that more and renewed efforts should be

undertaken to support further deepening and avoid heavy imbalances denying the

operation of a common space and its integration, in full.

It is a common knowledge in economic theory that peripheral and less advanced

economies cannot reach directly a takeoff stage, without passing from middle stages

(Rostow, 1960). A series of economic, political, institutional and other factors are tested

in such stages and their actual operation in practice, which however require the presence

of human forces inside domestic territories (or even their return) and not their migration

in other European spaces. Labour mobility and a brain drain may alter the direction of the

path pursued, if, for some reason, the prospect of a better future is not realistically

pictured. Such a transition from one stage to another brings further changes that unleash

economic and political forces operating in a way that has been called elsewhere “creative

destruction” (Schumpeter, 1942). Rather a “big push” is needed, as recommended in

economic theory for some of these economies, in order to draw high private sector

leverage not only of domestic origin and the operation in place of high added-value

investments, infrastructural development and planning, as well as the parallel

industrialisation across different industries (Rosestein-Rodan, 1943; Murphy et al, 1989).

According to economic theory, the spread of growth via small and medium sized

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enterprises will be helpful to sustain and localise wealth. This prospect could reduce

heavy current account imbalances among member-states and redress them, without

breaking the linkages created. Theoretically this view is further supported by the study of

a Keynesian model in states with large deficits, following which net exports are equal to

the net difference between saving and investments (Richardson, 1969).

Similar conclusions can be drawn using macroeconomic analysis. The basic

macroeconomic equation Y=C+I+G shows that in peripheral states facing problems,

when policies are implemented to reduce G and C, income can increase through

investments.

All open economies incorporated in a common currency area receive their international

interest rate. The more a less developed open economy will be requested to invest its

savings, public or private, the more these will tend to fall. The prospect of a large

absorption of savings at the periphery of a common currency area is pictured in

Appendix B.

Large amounts of savings, public and private, have been used for investment purposes, as

requested by the EU Cohesion Policy. The latter sought to enhance growth by supporting

peripheral governmental expenditure and increasing investments, both affecting

consumption. Significant funds were devoted in purchasing machines and tools from

other EU states. Other reasons for the large absorption of savings relate to the progressive

integration of economic space, the use of a common currency that uncovered growth

differences and removed concerns for exporting savings, the reduction of transaction

costs for transferring money and savings abroad and the competition from non-peripheral

financial and banking institutions offering higher profits for savings, as well as better

investment opportunities. The creation of new profit opportunities in financial activities is

likely to have acted addictively for larger parts of domestic populations seeking new

profit opportunities abroad rather than a long-term support of a productive path and an

increase of the propensity to save. The fall in savings could also relate to a

mismanagement of EU funds and to corruption, further affecting the availability of funds

17

for investment purposes and the propensity to invest. Furthermore, substantial parts of

savings are removed to off-shore firms and destinations outside the EU, benefiting at

large from the unionisation process and the free movement of capital.

The relation between savings and investments (whenever current accounts are included)

is seen in both identities below:

S = I + CA (i)

that leads to S - I = CA (ii) (Abel et al, 2006)

If S is reduced, current account deficits are expected to appear, as diagrammatically

represented by using the respective curves of S and I, at the current interest rate of a

common currency zone (Diagram A). According to (ii) a reduction of a large current

account deficit can take place by increasing savings (or reducing investments).

Assume one peripheral and small open economy at the Eurozone with large deficits, such

as the Greek. Its equilibrium point, if isolated from the rest of Eurozone states (without

affecting upon the Eurozone’s interest rate) would be formed at an upper left part of

Diagram A (7%), limiting its product. This is because its savings are very much limited,

followed by limited investments. Simultaneously, the interest rate is formed at the bottom

right part of the Diagram, for all investments and savings at the Eurozone (3%). Since

Greece receives its interest rate from the Eurozone, the higher interest rate in Diagram A

helps to explain a process of price rising in goods and services likely to be under

operation and excuses why they are more expensive than in other places of the Eurozone.

In the common currency area, increasing interest rates at the level of each state may not

become visible and early diagnosed through official inflation rates.

Policies reducing investments in this peripheral state will shift further the investment

curve to the left and downwards (from I1Gr to I2Gr), bringing, since savings are also

limited, an equilibrium closer to that at the Eurozone (assume at 5%). But investments

must continue to fall to reach the Eurozone level, bringing an extended recession.

18

Diagram B reflects similarly the IS curve for Greece and Eurozone, as synthesized by

their components in Diagram A (See Abel et al, 2006).

Diagram C helps to explain that the logic of the present argument favouring the

importance of investments -from the supply side- should be preferred from a money

market (LM) intervention. Assume the economy of a common currency area is at a

general equilibrium in point E, producing a product of full employment Y1, at a fixed

interest rate (3%) and price level. An increase in money supply because of a problem at

I2GR I1GR

SGR

Ieurzn Seurzn

ISGr

ISeurzn

Interest rate (r)

Y (product)

Diagram A

Interest rate (r)

Y (product)

Diagram B

7%

5%

3%

IS LM2

Real Interest rate (r)

Y (product)

Diagram C

LM1 FE2 FE1

Y1 Y2

E

F

3%

2%

19

the periphery (for example through issuing national or other common EU bonds), will

shift the LM curve to the right and downwards. The new LM2 curve will intersect the IS

curve at a point F, now giving a lower interest rate, 2%. By lowering the interest rate,

demand for goods in most advanced and central states will increase. If businesses will

decide to produce more products to cover the increased demand, the production (and

supply) will increase. The main problem is that such supply increases, taking place to the

benefit of businesses in central and advanced states, are not in new products but rather in

existing products, not incorporating new R&D and patents. This is because demand

increases send the signal that supply could be offered through the same products and

goods and that there is no actual need for changes.

Because aggregate demand is higher and the product is now at the point F, businesses

will increase their prices, bringing a shift from LM2 to LM1 and the supply of money

back to its original position. The economy will return at point E (and the respective

interest rate and product equilibriums), but through incorporating an increase in prices. In

practice, such price increases risk also breaking rather than sustaining the linkages

already formed across the EU economy, to the benefit of non-EU, international

competitors. An internal competitiveness problem will appear since production at the

periphery in some particular products and goods has already shifted away and is now

produced in central and advanced states. A part of this production will be finally

transferred outside the EU because of the incorporation of price increases. This could

take place by locating factories from central and advanced states in non-EU spaces.

Since peripheral and less advanced economies do not actually operate in full

employment, any appeal to supply-side policies would require labour market

interventions, following a Keynesian prescription for overcoming recession. The

application of such policies has a limited value in an environment that actually causes its

perpetuation and has no reason to continue if impoverishment is finally brought at some

part of this common space. Rather it will act as a migration-push force towards the

common space. Their application should rather be seen within the context of putting a

peripheral and less advanced economy back in motion in the short run, further acting, by

20

way of price reductions, as an attractive force for investments. However, particular

domestic conditions should also be considered, resulting from the crisis such as the

problem of transportation inside the domestic environment that is likely to affect

negatively any growth efforts and the circulation of labour and capital.

Assume that a combination of policies that reduce a current account deficit and structural

policies targeting at labour market reforms and the enhancing capital and labour

circulation are applied at a peripheral state, by the state itself or in association with the

common currency members. If such policies would be seeking to affect directly G and

indirectly I (for example by reducing bureaucratic or any labour obstacles and leaving

more room for the private sector), they should also be expected to negatively affect C.

For instance policies increasing tax rates could reduce consumption. Consumption will

fall for numerous reasons, including the lack of confidence, the worsening of

expectations, high household debts (at the aftermath of a crisis), as well as the lack of

willingness from the private sector to invest and replace the withdrawal of state from its

activities in the absence of any growth prospect. In the absence of a stable tax

environment, the efficiency of policies that raise taxes will be affected, especially if tax

rates are increased. Efforts to raise more taxes are likely to lead to tax evasion, if income

falls and the limited sources of income are mobile at the common space. Tax evasion may

derive from a domestic intergenerational conflict between a new generation being asked

to pay a large deficit created by the older generations, which however largely benefited

from the application of policies in the past (Rosen and Gayer, 2008). But it may also

derive from social and political groups benefiting from past policies, seeking further to

affect the application of policies for their own benefit. Overall, it appears that cutting

budget deficits alone, in the absence of investments, is unlikely to offer the appropriate

results, as it largely depends on many different parameters that may aggravate the effects

of such policies in the common space, carrying the prospect of a long-term recession in

practice.

Assume further that a peripheral economy witnesses a twin deficit (as Kosteletou (2012)

discusses in the case of Greece).

21

When splitting savings further into private (Sp) and public (Sg), (ii) leads to a basic

macroeconomic equation on the use of savings (Abel et al, 2006):

Sp = I - Sg + CA (iii)

This equation on the use of savings emphasizes that a large current account deficit can be

resolved by selling public property abroad and using savings from abroad. This is better

realised when public savings (Sg) are very low. However, the third component of the

equation is investments. Indeed, a current account balance can also be reduced if private

savings from abroad are used to drive investments.

After distinguishing investments into private (Ip) and public (Ig), it follows from (iii) that

CA = (Sp-Ip) + (Sg-Ig) and that

CA - (Sg-Ig) + Sp= Ip (iv)

It appears from equation (iv) that, under conditions of a twin deficit (referring to both CA

and Sg-Ig), a substantial absorption of both private and public savings (Sp and Sg) and

the lack of possibility to draw any further public investments (Ig), a long-term

perspective to reduce both deficits relates to the side of private investments that should

substantially enhance in the peripheral state in need.

Assume further from (iii) two states, one peripheral (1) and one central (2), such that

Sp1 = I1 - Sg1 + CA1

Sp2 = I2 - Sg2 + CA2

The latter equation can be re-written as

I2 = Sp2 + Sg2 - CA2

22

Tackling a current account deficit for a peripheral state from the investment side (I1)

would require drawing funds from a central state and invest them (I2). Assume a current

account surplus for the central state (CA2), because it draws income from its activities

targeted at the periphery. Any new investments in the peripheral state (I1) will continue to

offer a surplus, provided that they are in new products. Such investments do not

necessarily need to derive from governmental (public) savings (Sg2), especially given the

importance of using such funds for re-distributing wealth and income in domestic

societies (and the necessity of such policies for further consolidating the building of a

common space). It is mostly from private savings Sp2 (or other) that investments should

be driven.

Taken from a broader European perspective, such private investments should arrive back

to the periphery from those sources (firms, banks or others), located in EU central and

advanced states, which have benefited at large from savings out of the periphery, taking

advantage of capital freedom and the use of a common currency. Resolving what appears

to be a difficult puzzle relates to investing private EU savings at the EU periphery, where

the symptom appears, in high profit opportunity investments.

In a unified EU economic space, where established pan-European linkages allow strong

income leakages and diffusion outside the EU periphery, peripheral economies could

either reduce such leakages to some extent (which is rather a negative path to take,

opposing to their openness), via import substitution policies, direct or indirect or enhance

domestic income multiplication through inter-industrial diffusion (in other words to

increase the industrial and international Keynesian multipliers). The latter could increase

the EU and European value added, if carefully planned. Viewed from this perspective, the

EU is forming an internal space for investments with higher profit opportunities that

could both deliver and distribute growth and wealth across EU space. Such an investment

prospect should further be supported by infant industry protection and strategic trade for

the new industries.

23

In order to establish a more viable solution, it appears that private savings for a peripheral

state Sp1 that will be used for investments in new products should be larger than those

private savings from other central and advanced states, Sp2, and those from other

international savings, Sp3, such that profits shared out of this process are also ranked in

the same order (Sp1>Sp2>Sp3 such that Pr1>Pr2>Pr3)3.

The present solution emphasizes the necessity of private investments in peripheries to

organise growth and the undertaking of a certain risk from their side, before a twin deficit

is being transferred across the common currency area periphery. Other policy responses

to such twin deficits, such as those seeking to reduce public savings, cut investments and

balance the unbalanced current accounts by selling state’s property (looking at the second

side of equation (iii)), currently implemented, risk breaking the linkages formed in the

common EU and European space, bringing losses in the long-run for businesses from the

rest of the EU and the EU centres investing at the periphery. Similar historical efforts to

turn a current accounts balance to positive have appeared to offer mostly short-term

solutions (see in Abel et al, 2006). Investment in these peripheries, via new industries,

could drive their growth leading to convergence, before any adverse side effects of other

policies appear, reducing the profitability chances in these markets.

The success of the existing direction for the growth of the European economy could be

based on the model by Dixit & Stiglitz (1977) that considers growth to be the outcome of

investments in new, hybrid products, offering higher profits for businesses. This view has

been adopted by new economic geography, further recommending that growth in

peripheries should not contradict but rather strengthen that in centres, to be sustained on

both sides (Combes et al., 2008). Such investments and the resulting industrial support

and change in peripheries should target at a progressive transformation of economic

centres and reduce risks from various industrial paths taken that need change. Large-scale

investments in peripheral states and regions in projects creating new products of high

added value could bring a sufficient number of jobs and could drive, in a propulsive way,

3 Profits Pr2 and Pr3 do not include income leakages, which will expand the actual profits for central and

advanced states.

24

inter-industrial and inter-regional growth and its diffusion, if sustained by a large number

of small and medium sized enterprises. Attracting production and employment force in

peripheries that remain excluded or not expressed in central and wealthier areas is to the

benefit of Europe. Such manufacturing and large-scale business relocation policies that

could now take place at the pan-European level were, up to 1970s, the principal policy

paradigm in regional studies, inside national borders. This policy paradigm laid down the

growth foundations in most of the developed European regions today (see in Armstrong

and Taylor, 1999). By adopting a variety of incentives towards this recommended

direction, the EU could support young and dynamic industries at these economies, while

offering strategic trade support for infant industries, if needed. This could have helped to

better economise European wealth and prepare the EU for a new stage of economic

integration.

Stable levels of employment and output are needed for the appropriate operation and

deepening of the unification process. Stability is one of the three cornerstones before a

common fiscal policy across a unified currency area is implemented. This can be

achieved only after an extended period of application of common policies through the

other two important conditions, allocation and both income and wealth redistribution

(Musgrave, 1959). At early stages of integration, governmental taxes and expenditure

would tend to differ across the common currency space. Furthermore the appearance of

large deficits in balance of payments and current accounts, especially in those peripheral

and advanced states that have applied common policies and achieved to better integrate,

would tend to impede the achievement of macroeconomic stability. Reducing these

imbalances is necessary, making practically any conditionality on the creation of balance

surpluses (as recommended by the Stability and Growth Pact) a short-term measure.

Deepening integration towards the direction of fiscal integration highlights the need to

reduce such imbalances4. A long-term pursued EU Cohesion policy could be viewed as a

pioneer of a common fiscal policy, even though it represents a small proportion of total

output levels in peripheral and less advanced states and is subject to many policy

obstacles, especially those of growth orientation.

4 it is rather a positive surplus in the common balance of the currency zone that ought to be pursued

25

The withdrawal of savings at the geographical scale of the EU or Europe more broadly,

could be explained by a pan-European neoclassical-type shift of capital that increases

capital accumulation at the EU and European rather than at the state level. Capital

accumulation however is a very important precondition before implementing re-

allocation and allocative efficiency, as capital needs to expand before it is actually being

used for investment purposes at peripheral and less advanced states (so that such

investments reduce the risk of its minimisation or loss). As explained, it is mainly via the

private sector that such investments should take place. Directing EU growth will help to

move integration a step forward, while reaching new frontiers in the enlargement process.

5. Creating the prospect of a unified European cluster

The removal of professional barriers, which relate to political, economic, cultural or other

reasons and traditions could contribute to labour mobility and its attraction at the

periphery. Business association at the European level is needed in large-scale projects

offering a distinctively large number of jobs that would absorb large unemployment

levels in peripheries and reduce the effects of unbalanced growth from continuous growth

in some central and more advanced areas. Producing new products could create new

markets, without threatening the primacy of domestic industries in most advanced states.

The production of hybrid vehicles, such as hybrid helicopters, could resolve long-term

domestic transportation and labour movement problems in these countries, for example

those in Greece, as well as the fundamental problem of distant location of their

population and labour force from centres of consumption and production in Europe or

those of the wider geographical region. The production of such products covering

European needs could promote changes, progressively and over time and help the

transformation of production in production centres. Following this way, the demand of

one nation could be satisfied by the supply of another, while part of income created in

most advanced states via international trade could return in Europe via R&D investments.

The price falling tendency at the EU periphery after the world crisis could act

attractively, if combined with a middle or long term perspective for higher, directly

exploitable, profitability of the European businesses.

26

From this perspective, creating relations of trust and cooperation with economic interests

in central EU areas and associating with them is for the benefit of more peripheral EU

states. A better choice for peripheries is to engage in a role supportive or complementary

to centres not that as direct competitors, seeking to build coalitions of interests. Reaching

a point in European history at which such an association is feasible, had required the

creation of a demanding level of economic programming and state capacity building,

before policies implemented in peripheries are interwoven with those in growth centres.

An intensive learning period, progressively formed and prepared through EU policies,

was needed before reaching this point, binding different state, regional and local

economic programming and planning.

The theoretical underpinnings for such a direction could be found in the extended

discussion on clusters at the local and regional level and the formation of economic

relations of collaboration and cooperation in them (Crux and Texeira, 2010). The

question of how economies and economic actors associate is provided in various readings

concerning the industrial districts and the clusters (Marshall, 1920; Martin and Sunley,

2003). These are considered to act as drivers of national and regional competitiveness, in

many respects (Porter, 1998). Firms benefit from domestic agglomeration economies and

economies of scale, but the role of endogenous economic growth factors and that of

society is also emphasized in forms of “cooperative competition”. Synergistic relations of

trust and reciprocity, knowledge transfer, technology and R&D support, “untraded”

interdependencies among local actors and firms and the emphasis on human capital

support and interaction, endogenous growth factors, institutional building and

administration, fosters an industrial environment (“milieu”) conducive to growth (Asheim

et al., 2006; Martin and Sunley, 2003; Moulaert and Sekia, 2003; Kuah, 2002; Morgan,

1997; Granovetter, 1985). Clusters were suggested more recently to be a dynamic and

metaphorical construct that could be used more broadly (Vorley, 2008).

Various economic, political, social and other conditions are discussed as necessary for the

creation and operation of clusters. These appear to be based on a domestic family of

27

principles and perceptions for production and the economy, in the promotion of

innovation and knowledge, research and development, labour movements, the support of

small and medium sized enterprises and economic and social forces and institutions.

Institutions in particular act as a major catalyst for change and development in clusters, at

the local level. Under the prism of cluster theory, existing EU policies appear to have

prepared the ground towards this direction, by creating already many of the preconditions

of a common pan-European environment with similar characteristics. These could evolve

even further towards the direction of a cluster of pan-European radiation. This is better

realised, if, in retrospect, what separated and divided EU states in the past is compared

against the common points of contact formed among EU economies and the current

established perception of common EU economic interests.

6. Conclusions

The present proposal for the future of Europe emphasizes both the importance of the

foundations already created by the EU and the direction and conditions of transition

towards economic integration. It is highlighted that the EU rather than pursuing a model

of rivalry and competition among state economies, which enhances the “stones” at the

European edifice because of the emphasis put upon European competitiveness, should

rather turn more carefully towards a direction that emphasises and lays down the

connecting “material” of this edifice. This “material” is, to some extent, subjective, as it

relates to the geography and history of nations that have created conditions for this

progress and well-being. It also derives from their different customs, traditions and ethos

or other social, economic, political and other characteristics that are a part of the

European and human civilisation and wealth and a foundation stone upon which their

solidarity is created. What is suggested with the present announcement is the continuation

of an existing path towards a direction that cultivates even further an environment of

economic amyllae, which will provide more chances for a noble competition and

cooperation among European partners, offer chances of participation and expression in all

growth forces both in centres and peripheries in Europe and many chances to people for

succeeding. The foundations for the creation of such an environment have already been

28

created. They relate to the pre-discussed national and European foundations, the creation

of some form of unbalanced growth that needs to be reduced and that of propulsive

linkages among economies, the necessary institutions to sustain growth and more

generally numerous preconditions for the creation of a cluster at the pan-European level.

The existing direction relates to an increase of opportunities for competition at the

European periphery, the strengthening of relations of cooperation among European

economies, a better relation of peripheral with the European economy, the significance of

putting the right people at the right place and both in state and EU policy making roles,

and the creation of an environment that promotes less a harsh competition and more

economic amyllae. Even from the present viewpoint however, it is important to make

clear not only the limits of economic freedom, but also those of social cohesion and

stamina, especially for those opposing continuous social change. The latter is important

given the danger of loss of confidence regarding the economic, social and political forces

needed to operate change. For this purpose, it is appropriate to enable and promote at the

political level those forces and personnel inside societies that will undertake the task of

implementing such changes. These persons should relate to and express common

European interests, have to be capable of understanding better their common points, in

the long-run, the need for solidarity and a mutual support of European interests.

Institutional state organisation and state regimes, especially for newer and more

vulnerable democracies, are likely to affect policy effectiveness, acting as catalysts of

change.

7. EU policies and the European convergence; using a new methodology

The remaining of this paper discusses the results from the use of an innovative

methodology to test convergence in Europe. The previous conclusions and analysis were

based on these results.

Various studies use empirical evidence to assess convergence trends at the EU level.

Several methods have been suggested to measure convergence, such as modelling

29

(including input-output models), cost-benefit analyses, indices and various qualitative

assessments. Some of the studies using modelling offered evidence on EU-level

convergence (Sala-i-Martin, 1994 and 1996; Badinger et al, 2002; Gallo and Dall’erba,

2008; Cappellen et al, 2003). In some cases EU membership was associated with

convergence, especially for the poorer states (Cuaresma et al, 2008). Convergence

outcomes were espoused by official EU policy documentation, which made use of indices

to quantify the effect of EU policy making (COM 2002; 2004). Club, beta or sigma

convergence was discussed among states or regions and the prospect of divergence was

highlighted in few studies (Baumont et al., 2003; Cuadro-Roura, 2002). The neoclassical

framework was used to diagnose core-periphery imbalances in the EU or inside states

(Fingleton, 2003; Siriopoulos and Dimitriou, 1998) and their strengthening in peripheries

(Tsionas, 2002; Asteriou et al, 2002).

The present work contributes in the assessment literature by using an innovative

quantitative, non-modelling method to assess state-level convergence based on the

calculation of correlation coefficients for a panel of states, over the 2000-2008 period.

The Pearson correlation coefficients and their levels of significance are calculated,

together with the change in their significance over the study period. Pearson is preferred

from Spearman correlation coefficient, since the variables used are interval and, in the

vast majority of cases, normal, as indicated in the respective normal probability plots

(Appendix C)5. Pearson coefficients are also more sensitive to outliers and increases or

reduction in variables, such as in growth levels, which are necessary to capture and

measure divergence, for example when GDP or growth level outliers appear. The

coefficient of determination is calculated as the square of the correlation coefficient

(Rodger and Nicewander, 1988). Convergence is indicated after the calculation of

correlation levels and their change over the study period.

5 In those few cases were normality is not observed, results, as discussed below, should rather be

interpreted with scepticism. These are the cases of production variables (prodcom) and market integration

and FDI variables (inoutFDI, inFDI and outFDI). This is also observed for some of the years in the

variables used for the net balance of services, imports of services and exports of services (and more

specifically for variables from ntblsr0c02 to ntblsr0c08, from expsr0c02 to expsr0c08 and from impsr0c02

to impsr0c08).

30

The 2000-2008 period of initial implementation of the Euro-zone is selected, before the

beginning of the international crisis and the spread of its effects upon the EU economy

and periphery. State-level data are collected from Eurostat’s webpage for 34 countries in

geographical Europe. These comprise all EU member-states, EU candidates and states for

which data were available at Eurostat’s website6. The variables are either used as

provided or constructed (e.g. for prodcom variable). They are deflated if needed, using

official consumer price indices from Eurostat’s webpage or other official governmental

sources. All variables are turned constant for the initial year of study. Distance is drawn

from the Michelin guide and measured in kilometers from the city of Brussels, for each

state capital. Brussels is centrally situated in the London-Milan-Berlin triangle or the

EU’s “banana”, is the locus of EU political and administrative authorities and also

centrally situated among all six countries initially participating at the unification process.

8. Empirical Results and Evidence

Diagrams 1 and 2 indicate the distance in kilometres, time and costs of EU states

included in the study. Some suffer from an intensive geographical peripherality, while a

distinction can be made between a core of six EU states on the one hand side (Benelux,

France, Germany and the UK) and other states on the other, such as Greece, deviating

from average EU distance.

6 The non-EU countries included in the study are Iceland, Liechtenstein, Switzerland, Croatia, FYROM and

Turkey.

31

Diagram 1: Average deviation in distance of EU state capitals from Brussels

Average Deviation in Distance of EU countries from Brussels

(in km and min)

-1500 -1000 -500 0 500 1000 1500 2000

Greece

Romania

Bulgaria

Portugal

Lithuania

Latvia

Finland

Spain

Sweden

Hungary

Italy

Poland

Slovakia

Slovenia

Austria

Denmark

Czech Republic

Estonia

Ireland

Germany

France

United Kingdom

Netherlands

Luxembourg

EU

co

un

trie

s

Distance in km and minutes

Deviation of time distance from

EU average (min)

Deviation of space distance

from EU average (kms)

Source: Michelin guide, accessed on-line, 25

th of November 2010, Malta and Cyprus not

included (for Cyprus data were not available)

32

Diagram 2: Average deviation in distance costs of EU state capitals from Brussels

Deviation of Costs of Distance from EU average (in Euros)

-200 -100 0 100 200

Greece

Romania

Bulgaria

Portugal

Lithuania

Latvia

Finland

Spain

Sweden

Hungary

Italy

Poland

Slovakia

Slovenia

Austria

Denmark

Czech Republic

Estonia

Ireland

Germany

France

United Kingdom

Netherlands

Luxembourg

Co

un

trie

s

Deviation of Costs of Distance from EU

average (in Euros)

Deviation of Costs of Distance

from EU average (Euros)

Source: Michelin guide, accessed on-line, 25

th of November 2010, Malta and Cyprus not

included (for Cyprus data were not available)

33

Table 1a presents the correlations of distance from Brussels with all variables used in the

study. Their difference from the initial to the final year is seen in Table 1b.

Table 1a: Correlation coefficients of distance with all variables (bivariate correlations),

two-tailed tests of significance, t-values, standard deviations and levels of R-square

df=32 Correlation Coefficient

2-tailed significance

t Standard

deviation

R – square

GDPph01c -0.4863*** -3.1 16857.66 -0.236488

GDPph02c -0.4873*** -3.2 17095.95 -0.237461

GDPph03c -0.4962*** -3.2 16191.95 -0.246214

GDPph04c -0.4987*** -3.3 16369.99 -0.248702

GDPph05c -0.4904*** -3.2 16965.08 -0.240492

GDPph06c -0.4844*** -3.1 17834.47 -0.234643

GDPph07c -0.4794*** -3.1 18274.99 -0.229824

GDPph08c -0.4691*** -3 18167.94 -0.220055

GRr00 0.0618 0.35 1.850849 0.003819

GRr01 -0.0592 -0.34 2.922825 0.003505

GRr02 0.3672*** 2.23 2.360372 0.134836

GRr03 0.4306*** 2.7 2.698093 0.185416

GRr04 0.5151*** 3.4 2.199983 0.265328

GRr05 0.2812* 1.66 2.615942 0.079073

GRr06 0.2754* 1.62 2.584498 0.075845

GRr07 0.2713* 1.6 2.52783 0.073604

GRr08 0.2803* 1.6 3.264536 0.078568

Prodcom01 -0.3062** -1.8 1.74e+08 -0.093758

Prodcom02 -0.3155** -1.9 1.83e+08 -0.09954

Prodcom03 -0.3107** -1.8 1.89e+08 -0.096534

Prodcom04 -0.2965** -1.8 1.91e+08 -0.087912

Prodcom05 -0.3052** -1.8 2.01e+08 -0.093147

Prodcom06 -0.2924** -1.7 2.28e+08 -0.085498

Prodcom07 -0.2942** -1.7 2.48e+08 -0.086554

Prodcom08 -0.2941** -1.7 2.61e+08 -0.086495

VlFrTrlGDP01 0.2849* 1.7 5.117218 0.081168

VlFrTrlGDP02 0.4679*** 2.9 7.539015 0.21893

VlFrTrlGDP03 0.4728*** 3.0 9.965909 0.22354

VlFrTrlGDP04 0.5790*** 4.0 15.5709 0.335241

VlFrTrlGDP05 0.6617*** 5 21.66235 0.437847

VlFrTrlGDP06 0.5890*** 4.1 23.43956 0.346921

VlFrTrlGDP07 0.5773*** 4 25.45559 0.333275

VlFrTrlGDP08 0.5813*** 4.1 24.20329 0.33791

VlPsTrlGDP01 -0.0499 0.3 1.774007 -0.00249

VlPsTrlGDP02 -0.0703 0.4 3.604511 -0.004942

VlPsTrlGDP03 -0.0019 -0.001 5.044046 -3.61E-06

VlPsTrlGDP04 -0.0167 -0.09 6.465356 -0.000279

VlPsTrlGDP05 0.1032 0.59 7.397134 0.01065

VlPsTrlGDP06 0.1283 0.73 8.251228 0.016461

VlPsTrlGDP07 0.1395 0.8 9.785954 0.01946

VlPsTrlGDP08 0.1931 1.11 11.13023 0.037288

InOutFDI02 -0.4558*** -2.9 3.759168 -0.207754

InOutFDI03 -0.0090 -0.05 3.721416 -0.000081

34

InOutFDI04 -0.1622 -0.93 2.207273 -0.026309

InOutFDI05 -0.3376** -2.21 3.893774 -0.113974

InOutFDI06 0.1584 0.91 3.645993 0.025091

InOutFDI07 -0.3608*** -2.19 4.361192 -0.130177

InOutFDI08 0.2169* 1.26 2.341273 0.047046

outFDI02 -0.5413*** -3.7 2.451103 -0.293006

outFDI03 -0.2439* -1.4 3.604382 -0.059487

outFDI04 -0.5263*** -3.5 2.947057 -0.276992

outFDI05 -0.6380*** -4.7 4.54451 -0.407044

outFDI06 -0.6408*** -4.7 3.279424 -0.410625

outFDI07 -0.6789*** -5.2 4.511815 -0.460905

outFDI08 -0.6357*** -4.7 2.377934 -0.404114

inFDI02 -0.3583*** -2.2 6.249696 -0.128379

inFDI03 0.1313 -0.8 4.829816 0.01724

inFDI04 0.2315* -1.4 4.259883 0.053592

inFDI05 0.0367 -0.2 6.560904 0.001347

inFDI06 0.4263* 2.7 7.331212 0.181732

inFDI07 -0.0496 -0.28 6.726843 -0.00246

inFDI08 0.5087*** -3.34 4.801815 0.258776

fGFC01 -0.5415*** -3.6 2398.08 -0.293222

fGFC02 -0.5395*** -3.6 2362.807 -0.29106

fGFC03 -0.5281*** -3.5 2274.697 -0.27889

fGFC04 -0.5292*** -3.5 2371.518 -0.280053

fGFC05 -0.5228*** -3.5 2538.432 -0.27332

fGFC06 -0.5202*** -3.5 2694.465 -0.270608

fGFC07 -0.5095*** -3.4 2830.47 -0.25959

fGFC08 -0.5097*** -3.4 2739.586 -0.259794

CnFC01 -0.3932*** -2.4 0.0018382 -0.154606

CnFC02 -0.3891*** -2.4 0.0018923 -0.151399

CnFC03 -0.3936*** -2.4 0.0018287 -0.154921

CnFC04 -0.3968*** -2.4 0.0018276 -0.15745

CnFC05 -0.3979*** -2.4 0.0018601 -0.158324

CnFC06 -0.3989*** -2.4 0.0018807 -0.159121

CnFC07 -0.3886*** -2.4 0.0019276 -0.15101

CnFC08 -0.3804*** -2.4 0.0019944 -0.144704

LC_ind0c01 -0.0209 -1.1 2.999187 -0.000437

LC_ind0c02 -0.2334* -1.4 3.383343 -0.054476

LC_ind0c03 -0.1055 -0.6 4.01226 -0.01113

LC_ind0c04 -0.1235 -07 4.29291 -0.015252

LC_ind0c05 0.1568 0.9 5.083728 0.024586

LC_ind0c06 0.1044 0.6 7.16109 0.010899

LC_ind0c07 0.1621 0.9 11.37227 0.026276

LC_ind0c08 0.2143* 1.2 15.5807 0.045924

HTExp_TExp00 -0.1980 -1.1 13.91522 -0.039204

HTExp_TExp01 -0.2423 -1.4 12.83414 -0.058709

HTExp_TExp02 -0.2110* -1.2 12.12301 -0.044521

HTExp_TExp03 -0.1755 -1 11.37353 -0.0308

HTExp_TExp04 -0.1818 -1 11.11732 -0.033051

HTExp_TExp05 -0.2297 -1.3 10.27991 -0.052762

HTExp_TExp06 -0.1772 -1 10.94497 -0.0314

GDERDshGDP00 -0.5185*** -3.43 0.8005907 -0.268842

GDERDshGDP01 -0.5218*** -3.46 0.8085502 -0.272275

GDERDshGDP02 -0.5007*** -3.3 0.8227117 -0.2507

35

GDERDshGDP03 -0.5046*** -3.3 0.845122 -0.254621

GDERDshGDP04 -0.4958*** -3.2 0.8274536 -0.245818

GDERDshGDP05 -0.4847*** -3.1 0.8221751 -0.234934

GDERDshGDP06 -0.4821*** -3.1 0.8086237 -0.23242

GDERDshGDP07 -0.4527*** -2.9 0.8057081 -0.204937

GDERDshGDP08 -0.4127*** -2.6 0.8622617 -0.170321

ntblgd00 -0.3220** -1.9 2.289669 -0.103684

ntblgd0c01 -0.3140** -1.9 2.349667 -0.098596

ntblgd0c02 -0.3088** -1.8 2.331184 -0.095357

ntblgd0c03 -0.3518*** -2.2 2.141962 -0.123763

ntblgd0c04 -0.3531*** -2.2 2.133598 -0.12468

ntblgd0c05 -0.3403*** -2.1 2.360799 -0.115804

ntblgd0c06 -0.3147** -1.9 2.558156 -0.099036

ntblgd0c07 -0.3369*** -2 2.34418 -0.113502

ntblgd0c08 -0.3085** -1.8 2.834932 -0.095172

expgd00 -0.4656*** -3 5.325225 -0.216783

expgd0c01 -0.4937*** -3.2 5.378309 -0.24374

expgd0c02 -0.4913*** -3.2 5.166339 -0.241376

expgd0c03 -0.5215*** -3.5 4.61757 -0.271962

expgd0c04 -0.5430*** -3.7 4.674543 -0.294849

expgd0c05 -0.5473*** -3.7 5.038229 -0.299537

expgd0c06 -0.5546*** -3.8 5.38177 -0.307581

expgd0c07 -0.5634*** -3.9 5.385204 -0.31742

expgd0c08 -0.5493*** -3.7 5.690388 -0.30173

impgd00 -0.4827*** -3.1 3.647495 -0.232999

impgd0c01 -0.5437*** -3.7 3.553746 -0.29561

impgd0c02 -0.5579*** -3.8 3.317568 -0.311252

impgd0c03 -0.5633*** -3.9 2.966837 -0.317307

impgd0c04 -0.5901*** -4.1 3.051671 -0.348218

impgd0c05 -0.5985*** -4.3 3.300513 -0.358202

impgd0c06 -0.6126*** -4.4 3.58507 -0.375279

impgd0c07 -0.6052*** -4.3 3.734047 -0.366267

impgd0c08 -0.6002*** -4.4 3.783107 -0.36024

ntblsr00 0.2458* 1.4 0.8733137 0.060418

ntblsr0c01 0.2567* 1.5 0.8823724 0.065895

ntblsr0c02 0.2860* 1.7 0.8627244 0.081796

ntblsr0c03 0.3025** 1.8 0.7066864 0.091506

ntblsr0c04 0.3052** 1.8 0.6677465 0.093147

ntblsr0c05 0.2829* 1.7 0.6536196 0.080032

ntblsr0c06 0.2442* 1.4 0.5821429 0.059634

ntblsr0c07 0.1996 1.5 0.5202124 0.03984

ntblsr0c08 0.2412* 1.4 0.6458442 0.058177

expsr00 -0.3593*** -2.2 1.452847 -0.129096

expsr0c01 -0.3670*** -2.3 1.727101 -0.134689

expsr0c02 -0.3583*** -2.2 1.756763 -0.128379

expsr0c03 -0.3645*** -2.2 1.898136 -0.13286

expsr0c04 -0.3457** -2.1 2.040265 -0.119508

expsr0c05 -0.3447** -2.1 2.254376 -0.118818

expsr0c06 -0.3259** -2 2.54941 -0.106211

expsr0c07 -0.3069** -1.8 2.821112 -0.094188

expsr0c08 -0.3016** -1.8 2.805251 -0.090963

impsr00 -0.3937*** -2.4 1.816169 -0.155

impsr0c01 -0.3814*** -2.3 2.187099 -0.145466

36

impsr0c02 -0.3852*** -2.4 2.238827 -0.148379

impsr0c03 -0.3814*** -2.4 2.266972 -0.145466

impsr0c04 -0.3814*** -2.4 2.339897 -0.145466

impsr0c05 -0.3742*** -2.3 2.495972 -0.140026

impsr0c06 -0.3551*** -2.2 2.661527 -0.126096

impsr0c07 -0.3478*** -2.1 2.733242 -0.120965

impsr0c08 -0.3434** -2.1 2.814569 -0.117924

* 0.2 ≥ p ≥ 0.1, ** p ≥ 0.05, *** p ≥ 0.01

Table 1b: Significance and z-scores of the difference of the correlation coefficient

between two variables Variable A Variable B Z

GDPph01c GDPph08c -0.09

GDPph01c GDPph07c -0.04

GRr00 GRr08 -0.89

GRr00 GRr07 -0.85

Prodcom01 Prodcom02 -0.05

VlFrTrlGDP01 VlFrTrlGDP08 -1.46*

VlPsTrlGDP01 VlPsTrlGDP08 -0.97

InOutFDI02 InOutFDI08 -2.8***

outFDI02 outFDI08 0.57

inFDI02 inFDI08 -3.68***

fGFC01 fGFC08 -0.17

CnFC01 CnFC08 -0.06

LC_ind0c01 LC_ind0c08 -0.94

HTExp_TExp06 HTExp_TExp06 -0.08

GDERDshGDP00 GDERDshGDP08 -0.53

ntblgd00 ntblgd0c08 -0.06

expgd00 expgd0c08 0.44

impgd00 impgd0c08 0.66

ntblsr00 ntblsr08 0.02

expsr00 expsr08 -0.26

impsr00 impsr08 -0.23

* 0.2 ≥ p ≥ 0.1, ** p ≥ 0.05, *** p ≥ 0.01

Peripheral European states appear to achieve enhanced growth rates and sustain a positive

balance of services. The positive correlation of distance with the net balance of services

is likely to reflect the service-oriented character of peripheral states, for example in

tourism or real-estate and the opening, through unification, of European demand for the

provision of services in peripheral states. Such services may not be necessary high-tech

or high value added, but of low quality. But the differences of correlation coefficients for

these variables are not significant, reflecting non significant changes at the balance of

services.

37

Similarly the differences of correlation coefficients of distance with net balances, exports

and imports both for trade and services are not significant. The correlation of exports of

goods (expgd) with distance is highly significant, negative and high, changing to even

more negative. This is likely to reflect the exporting strength of central European areas

enhancing at the expense of more peripheral, even though the difference of the

correlation coefficient is not significant. The negative correlation of distance with the net

balance of goods (ntblgd) shows that more peripheral states benefit less in balance terms.

Net balances of goods reduce to the benefit of peripheral states, but do not significantly

change.

The positive and highly significant correlation of distance with freight volume transport

relative to GDP reflects freight transport increases in peripheral states across Europe and

the delivery of an improved European transportation infrastructure. The difference of

correlation coefficient is also not significant, even though at a lower level of significance.

Such results, taken together, could be an indication that the further away is a state from

Brussels the more is the freight transportation (relative to GDP), which further indicates

the strengthening of important role of trade in Europe, especially in peripheral states.

The correlation of distance from Brussels with market integration index (inoutFDI) and

inward FDI ranges from negative to positive and is rather inconclusive, even though the

difference in the correlation coefficients are highly significant. It appears that ever since

2000 and the enhancing of the European market integration, significant changes occur in

FDI in Europe, benefiting the penetration of European capital in peripheral states. But it

is not certain from existing data whether such capital has a long-term investment

behaviour at the periphery or whether it prefers a speculative, short-term presence. The

intense, insignificant for several years, fluctuation of the correlation coefficient of inward

FDI (as opposed to a more steady increase and the permanent, high significance of

outward FDI) is likely to reflect speculative movements of capital at the European

periphery, for example occurring from fund movements in stock markets. This could be a

rather dangerous picture. Absorbing EU funds in all peripheral states in the two

programming periods (2000-2006 and 2007-2013) could also affect these fluctuations,

38

since the transfer of EU funds through regional and cohesion policies are calculated in

FDI movements.

Manufacturing production (prodcom) does not significantly change from the initial to the

final year.

The levels of correlation coefficients of distance from Brussels with Gross Domestic

Expenditure on R&D measured as a proportion of GDP, GDP levels, Gross Fixed Capital

formation and Fixed Capital consumption appear to change to the benefit of peripheral

states. But the respective correlation coefficients reflect the presence of intense core-

periphery imbalances and none of their differences over the study period is significant (in

Table 1b).

The levels of GDP per head show that the EU centres appear to sustain a strong position

against the European periphery in growth level terms, despite an EU emphasis upon

policies at the periphery and the funds devoted for this purpose. Peripheral states fail to

overcome a growth threshold necessary to reduce the intensity of core-periphery

imbalances in Europe.

The correlation coefficient of distance with growth rates though positive for 2002, 2003,

2004, fall in the following period. This reflects a problem with sustaining relative higher

growth rates at the periphery, which could have brought a relative convergence. The

falling of the correlation coefficients of distance with growth rates, are coupled with non

significant differences in correlation coefficients, which highlighted the limited prospects

of convergence among European economies.

There is a strong negative correlation of distance with GDERDshGDP to the benefit of

central states. The correlation reduces over time, revealing the success of respective

endogenous growth policies for more central states. As the difference of the correlation

coefficient is not significant, it appears that more remains to be done on that direction.

39

Furthermore, central states appear to sustain a higher level fixed capital formation that

emphasizes their role as centres. Such an outcome could relate to an enhanced productive

capacity and the level of productivity, but also reflects that more value added is invested

in centres7. Similarly the correlation of distance with the consumption of fixed capital

over the study period is highly significant and negative. This indicates that the further

away from Brussels is a state, the less is domestic fixed capital consumption. Therefore

capital depreciates faster in centres and costs of production renewal are higher in them.

A glance at the evidence provided in Table 1a, shows that even though the EU appears to

have a certain capacity to redress European core-periphery imbalances, changes in the

correlation coefficients over the study period are not significant (Table 1b) and therefore

the forces of strong core-periphery imbalances remain under operation, causing spatially

unbalanced growth in Europe and probably inside states as well. Throughout the study

period -that coincides with the creation of the monetary zone- policies do not seem to

operate as much as needed to significantly bridge the gaps and achieve convergence.

Despite the intensity and range of changes implemented inside the EU, there is a clear

issue with EU policies followed that do not seem to bring substantially higher growth

rates at the EU or European periphery, necessary for strengthening their economies and

achieving converge. If the target is to create one Europe by reducing geographical

imbalances across its space, especially with regard to central-peripheral imbalances, the

combined evidence in Table 1a and 1b should lead to skepticism on the actual effects of

policies and their implications in reality. The overall picture is that the EU fails to deliver

substantial growth rates and the value added at European peripheral states needed to

expand exports and improve their balances in trade and services. Data show that central

states benefit more from the unification process, to the detriment of peripheral states. But

centrally located and advanced states may benefit at the period without participating at

the EU. Indeed, in Diagram 3 it appears that centrally located and advanced non-EU

7 GFC shows how much of the new value added is invested. CGFC shows how fast the capital is

depreciated.

40

states, such as Norway and Liechtenstein (with an initially high GDP per head in 2001)

benefit mostly in the study period, as reflected in the change of GDP per head.

Diagram 3: Change in GDP per head for EU and non-EU states

BLBL

CZDN

GER

EST

IRGR

SP FRIT

CYLTVLTH

LXB

HNGML

NTHAU

POL

PORRM

SLV

SLK FNSW

UK

gdpph01c

gdpph08c01

0 50000

0

10000

20000

IC

LCH

NR

SZCR

TU

gdpph01c

gdpph08c01

0 50000 100000

-10000

0

10000

20000

EU nonEU

Graphs by EU_memb

In Tables 2a and 2b we focus on the correlation of growth rates with the rest of the

variables. More light can be shed on the picture of correlation after remarking that growth

rates correlate negatively with GDP per head, at a high level of significance. That is to

say that more advanced states have reduced growth rates. The reduction of these

correlation levels over time could reflect upon the strength of some advanced states

managing to achieve higher growth rates (as it also appears from Diagram 3), even

though such increases may not be wide enough to make significant the difference of the

respective correlation coefficient.

The negative correlation of growth rates with the volume of freight transport relative to

GDP, though it fluctuates over the study period remains negative. The difference of

respective correlation coefficients is highly significant (from 2001 to 2008). Such

correlations are more likely to point at the fact that states with reduced growth rates

41

(generally the more advanced, as recommended above) have higher volume of freight

transport (as a percentage of GDP). This could relate, on the one hand side, to the

reduced impact of infrastructure built in peripheral states upon their growth rates and the

enhancing of domestic interregional and international mobility or, on the other, to the

competitive advantage formed to the benefit of trade from states of reduced growth rates.

The respective coefficients for the exports and imports of goods are negative and highly

significant, especially for the 2002-2006 period, while the balance of goods offers

negative correlation coefficients, whose difference is not highly significant for the 2000-

2006 period. Such correlation coefficients should emphasize that states of higher growth

rates are more likely to redress their balance of goods, avoid any insufficiencies in the

provision of goods and the upset of the current accounts.

The negative correlation of growth rates with GDERDshGDP is further intensified. This

could reveal that R&D taking place in states of reduced growth rates and those supporting

endogenous growth via policies, acts to their benefit and probably at the expense of less

technologically advanced states. But the difference of correlation coefficient is not

significant for the sample of all European countries as a whole. This could reflect

problems from emphasizing endogenous growth and related policies only in advanced

states, which may finally not deliver an outcome beneficial for Europe as a whole. More

expenses on R&D may be needed. The correlation of higher technology exports as a

percentage of total exports (HTExp_TExp) with growth rates fluctuates and changes from

positive to negative. This could reflect that states with reduced growth rates, probably

among those promoting more endogenous growth policies, achieve to export a larger

percentage of technology added products.

Taken together, evidence on the correlation of distance and that of growth rates reveals

the benefits brought by trade in some states, against peripheral production and those

achieving higher growth rates. It is likely that a duality is formed or revealed in the

European economy, favoring some more advanced and centrally located states that

produce goods of higher technology, benefiting more from R&D policies.

42

Table 2a: Correlation coefficients of Growth Rates with the rest of the variables

df=32 Correl. Coeff. 2-

tailed sign.

t Standard

deviation

R – square

GDPph01c -0.2281 -1.325 13085.2 -0.05203

GDPph02c -0.5279*** -3.516 13401.96 -0.278678

GDPph03c -0.6096*** -4.35 13334.99 -0.371612

GDPph04c -0.4582*** -2.916 13655.26 -0.209947

GDPph05c -0.3742** -2.283 14435.7 -0.140026

GDPph06c -0.5109*** -3.362 15005.43 -0.261019

GDPph07c -0.3395*** -2.042 15450.84 -0.11526

GDPph08c -0.2388* -1.391 15169.35 -0.057025

VlFrTrlGDP01 -0.2794* -1.646 5.357111 -0.078064

VlFrTrlGDP02 -0.6104*** -4.359 7.462534 -0.372588

VlFrTrlGDP03 -0.5516*** -3.741 9.864631 -0.304263

VlFrTrlGDP04 -0.4401*** -2.773 15.71791 -0.193688

VlFrTrlGDP05 -0.4436*** -2.8 21.08554 -0.196781

VlFrTrlGDP06 -0.5619*** -3.843 23.3759 -0.315732

VlFrTrlGDP07 -0.3659*** -2.224 25.3045 -0.133883

VlFrTrlGDP08 -0.1335 -0.762 23.68023 -0.017822

VlPsTrlGDP01 -0.2215 -1.285 1.938543 -0.049062

VlPsTrlGDP02 0.1251 0.713 3.775464 0.01565

VlPsTrlGDP03 0.2285* 1.328 5.169238 0.052212

VlPsTrlGDP04 0.1567 0.898 6.34788 0.024555

VlPsTrlGDP05 -0.0263 -0.149 7.269607 -0.000692

VlPsTrlGDP06 -0.0206 -0.117 8.183015 -0.000424

VlPsTrlGDP07 0.0044 0.025 9.420129 1.94E-05

VlPsTrlGDP08 0.4703*** 3.015 10.70138 0.221182

InOutFDI02 0.1113 0.634 108.2556 0.012388

InOutFDI03 -0.1203 -0.685 65.62105 -0.014472

InOutFDI04 0.0457 0.259 48.20872 0.002088

InOutFDI05 0.0974 0.554 64.46886 0.009487

InOutFDI06 -0.0025 -0.014 57.24978 -6.25E-06

InOutFDI07 0.1233 0.703 89.65543 0.015203

InOutFDI08 0.0406 0.23 40.85154 0.001648

outFDI02 0.0989 0.562 115.761 0.009781

outFDI03 -0.1315 -0.75 70.76493 -0.017292

outFDI04 0.0260 0.147 50.94433 0.000676

outFDI05 0.0752 0.427 68.39839 0.005655

outFDI06 -0.0208 -0.118 55.35354 -0.000433

outFDI07 0.1077 0.613 107.098 0.011599

outFDI08 0.0065 0.037 47.04136 4.23E-05

inFDI02 0.1097 0.624 103.2987 0.012034

inFDI03 -0.1189 -0.677 62.06766 -0.014137

inFDI04 0.0525 0.297 46.71131 0.002756

inFDI05 0.1153 0.657 62.22153 0.013294

inFDI06 0.0023 0.013 60.57909 5.29E-06

inFDI07 0.1285 0.733 74.65783 0.016512

inFDI08 0.0592 0.335 35.91137 0.003505

fGFC01 -0.1945 -1.122 2715.151 -0.03783

fGFC02 -0.4605*** -2.935 2690.084 -0.21206

fGFC03 -0.5558*** -3.782 2670.678 -0.308914

fGFC04 -0.4157*** -2.586 2766.413 -0.172806

fGFC05 -0.2492* -1.456 3042.092 -0.062101

43

fGFC06 -0.4331*** -2.718 3208.038 -0.187576

fGFC07 -0.2598* -1.522 3332.782 -0.067496

fGFC08 -0.2332* -1.357 3107.483 -0.054382

CnFC01 -0.4841*** -3.13 .0019673 -0.234353

CnFC02 -0.5385*** -3.615 .0019629 -0.289982

CnFC03 -0.6759*** -5.188 .0018974 -0.456841

CnFC04 -0.5126*** -3.377 .0019228 -0.262759

CnFC05 -0.5106*** -3.359 .0019481 -0.260712

CnFC06 -0.5649*** -3.873 .0019908 -0.319112

CnFC07 -0.4641*** -2.964 .0020496 -0.215389

CnFC08 -0.0841 -0.477 .0021478 -0.007073

HTExp_TExp00 0.4293* 2.689 10.15883 0.184298

HTExp_TExp01 -0.0123 -0.07 10.00485 -0.000151

HTExp_TExp02 -0.1529 -0.875 9.103206 -0.023378

HTExp_TExp03 -0.3494*** -2.109 8.554381 -0.12208

HTExp_TExp04 -0.4800*** -3.095 8.221019 -0.2304

HTExp_TExp05 -0.2231 -1.295 9.541721 -0.049774

HTExp_TExp06 -0.2964*** -1.756 9.175377 -0.087853

GDERDshGDP01 -0.2794* -1.646 .8050052 -0.078064

GDERDshGDP02 -0.6104*** -4.359 .8169041 -0.372588

GDERDshGDP03 -0.5516*** -3.741 .836396 -0.304263

GDERDshGDP04 -0.4401*** -2.773 .8171285 -0.193688

GDERDshGDP05 -0.4436*** -2.8 .8111644 -0.196781

GDERDshGDP06 -0.5619*** -3.843 .7990605 -0.315732

GDERDshGDP07 -0.3659*** -2.224 .797811 -0.133883

GDERDshGDP08 -0.1335 -0.762 .854031 -0.017822

ntblgd00 0.2140 1.239 2.415714 0.045796

ntblgd0c01 -0.0625 -0.354 2.506209 -0.003906

ntblgd0c02 0.0156 0.088 2.507495 0.000243

ntblgd0c03 -0.2054 -1.187 2.279719 -0.042189

ntblgd0c04 -0.1574 -0.902 2.29284 -0.024775

ntblgd0c05 -0.1216 -0.693 2.483764 -0.014787

ntblgd0c06 -0.2454* -1.432 2.690834 -0.060221

ntblgd0c07 -0.2209 -1.281 2.543761 -0.048797

ntblgd0c08 -0.1529 -0.875 3.105224 -0.023378

expgd00 0.1847 1.063 5.374649 0.034114

expgd0c01 -0.0706 -0.4 5.437823 -0.004984

expgd0c02 -0.2281* -1.325 5.23163 -0.05203

expgd0c03 -0.4331*** -2.718 4.691638 -0.187576

expgd0c04 -0.4641*** -2.964 4.755957 -0.215389

expgd0c05 -0.2933** -1.735 5.114618 -0.086025

expgd0c06 -0.3745*** -2.285 5.479576 -0.14025

expgd0c07 -0.2902** -1.715 5.492918 -0.084216

expgd0c08 -0.2340* -1.362 5.772215 -0.054756

impgd00 0.1385 0.791 3.548073 0.019182

impgd0c01 -0.0646 -0.366 3.524032 -0.004173

impgd0c02 -0.3718*** -2.266 3.294316 -0.138235

impgd0c03 -0.5374*** -3.605 2.931921 -0.288799

impgd0c04 -0.6126*** -4.384 3.032344 -0.375279

impgd0c05 -0.3705*** -2.256 3.291165 -0.13727

impgd0c06 -0.3972*** -2.448 3.581771 -0.157768

impgd0c07 -0.2860* -1.688 3.733317 -0.081796

impgd0c08 -0.2350* -1.368 3.790192 -0.055225

44

ntblsr00 0.1847 1.063 1.071913 0.034114

ntblsr0c01 -0.0706 -0.4 1.111745 -0.004984

ntblsr0c02 -0.2281* -1.325 1.177801 -0.05203

ntblsr0c03 -0.4331*** -2.718 1.009521 -0.187576

ntblsr0c04 -0.4641*** -2.964 .9583589 -0.215389

ntblsr0c05 -0.2933** -1.735 .9483124 -0.086025

ntblsr0c06 -0.3745*** -2.285 .9141298 -0.14025

ntblsr0c07 -0.2902** -1.715 .8879172 -0.084216

ntblsr0c08 -0.2340* -1.362 1.125423 -0.054756

expsr00 0.1257 0.717 1.573749 0.0158

expsr0c01 -0.0118 -0.067 1.842778 -0.000139

expsr0c02 -0.2104 -1.217 1.980213 -0.044268

expsr0c03 -0.3100** -1.844 2.078871 -0.0961

expsr0c04 -0.3350** -2.011 2.373346 -0.112225

expsr0c05 -0.1865 -1.074 2.19291 -0.034782

expsr0c06 -0.3121** -1.858 2.640078 -0.097406

expsr0c07 -0.2389* -1.392 2.90534 -0.057073

expsr0c08 -0.3253** -1.946 3.005969 -0.10582

impsr00 0.2872* 1.696 1.814288 0.082484

impsr0c01 0.0243 0.138 2.186417 0.00059

impsr0c02 -0.0724 -0.411 2.243374 -0.005242

impsr0c03 -0.2476* -1.446 2.27427 -0.061306

impsr0c04 -0.2874* -1.697 2.345638 -0.082599

impsr0c05 -0.1333 -0.761 2.498683 -0.017769

impsr0c06 -0.2618* -1.534 2.656593 -0.068539

impsr0c07 -0.2217 -1.286 2.72734 -0.049151

impsr0c08 -0.3853*** -2.362 2.821305 -0.148456

* 0.2 ≥ p ≥ 0.1, ** p ≥ 0.05, *** p ≥ 0.01

Table 2b: Change in the correlation coefficients of growth rate Variable A Variable B z-score

2-tailed significance

GDPph01c GDPph08c 0.04

prodcom01 prodcom06 0.16

prodcom01 prodcom08 -1.05

VlPsTrlGDP01 VlPsTrlGDP08 -0.6

VlPsTrlGDP01 VlPsTrlGDP06 1.37*

VlFrTrlGDp01 VlFrTrlGDp08 -2.9***

VlFrTrlGDp01 VlFrTrlGDp06 -0.81

InOutFDI02 InOutFDI08 0.26

outFDI02 outFDI08 0.34

inFDI02 inFDI08 0.19

fGFC01 fGFC08 -0.07

fGFC01 fGFC06 0.98

CnFC01 CnFC08 -2.47***

CnFC01 CnFC06 0.02

LC_ind0c01 LC_ind0c08 -0.71

LC_ind0c01 LC_ind0c06 -2.65***

HTExp_TExp00 HTExp_TExp06 3.01***

GDERDshGDP01 GDERDshGDP08 -0.6

ntblgd00 ntblgd0c08 1.46*

ntblgd00 ntblgd0c06 1.84**

ntblsr00 ntblsr0c08 -2.14***

45

ntblsr00 ntblsr0c06 -0.81

expgd00 expgd0c08 1.67*

expgd00 expgd0c06 2.29***

expsr00 expsr0c08 1.83**

expsr00 expsr0c06 1.77**

impgd00 impgd0c08 1.49*

impgd00 impgd0c06 2.2***

impsr00 impsr0c08 2.22***

impsr00 impsr0c06 2.76***

* 0.2 ≥ p ≥ 0.1, ** p ≥ 0.05, *** p ≥ 0.01

As opposed to the picture of the correlations with distance, most of the correlations of

GDP per head (Table 3a) are positive and highly significant. This highlights the clear

role undertaken by the more advanced states in driving the European economy and its

growth.

Negative are the correlations of GDP per head with the volume of freight transportation

relative to GDP (VlFrTrlGDP) and the balance of services (ntblsr). The former

correlation turns to negative and highly significant, while the difference of the correlation

coefficient is also significant. This should reflect upon the fact that increased trade takes

place in states of lower growth levels, which are exposed and more vulnerable to trade

openness.

The correlation coefficients for inward, outward FDI and market integration index are all

high, positive and highly significant. Although they all change to the benefit of advanced

states, the differences of their correlation coefficients are not significant. Given that EU

Cohesion and Common Agricultural policies transfer funds to less advanced states, the

results practically reflect an advantageous position of advanced states as both FDI

recipients and senders and as places of enhanced market integration. The less advanced

states do not benefit from the unification processes and it appears that the less advanced

is a country the less important is its position as FDI sender, recipient and as a market

integration place. Such results should be treated with more scepticism, given the problem

of normality identified before.

46

The correlation coefficients for GDP per head with gross fixed capital formation and the

fixed capital consumption are all positive, extremely high and highly significant.

Similarly are the respective coefficients of determination. The picture appears to reveal

that, despite efforts for capital accumulation at the EU periphery, the European capital is

formed and consumed in most advanced states, sustaining a leading role in forming and

consuming it. This is substantial evidence on the existing very large gaps in the formation

of capital between the less and more wealthy states. It appears that the unification and

integration process at the study period and earlier does not affect this picture and is rather

acting to the benefit of the formation of capital in advanced and wealthier states. Since

the difference in the correlation coefficients for both variables are not significant, it

appears that the EU fails to change towards a direction that would reduce the strength of

this correlation, at least marginally. Economic conditions and large economies of scale in

European centres, continuously attracting capital and labour from the European periphery

after the opening of EU and European borders, sustain their role as attractive places to

work and live in. Despite policies pursued at the study period in EU periphery, the overall

value added created at the less advanced states appears to have no significant change to

their benefit. On the contrary the opposite argument could be hold on the sustaining and

enhancing of the competitive strength of advanced European states and their capacity to

form the new value added. Taken from this perspective, the unification process appears to

have benefited mostly the advanced states, irrespective of EU membership and to cause

further problems and the relative impoverishment of the less advanced states.

There is no evidence from the present analysis concerning the benefits extracted from the

largest capital from capital formation and accumulation process in advanced states. This

might be for example at the expense of smaller businesses. Neither any conclusion can be

drawn on whether additional wealth created from value added increases is equally spread

socially and spatially. These are important points to be studied further and are of special

importance and interest in the light of the policy recommendations made in the present

text.

47

The correlation coefficients GDP per head with exports, imports and net balances of

goods are all positive, highly significant and high. The correlation of exports of goods is

very high and enhances, reflecting the strength of the position of more advanced states.

The correlation of imports of goods fluctuates and reduces only marginally, remaining

however in equally high levels. This point remarks that advanced states are also large

importers of goods. The correlation of the net balance of goods is strengthened to the

benefit of advanced states, reflecting upon deficit problems in balances of goods in

several states. All these changes however are not significant, as seen in the difference of

correlation coefficients.

The correlation coefficients for the exports and imports of services appear to reduce. The

non-significant correlation of GDP levels with the net balance of services also falls,

benefiting more advanced states. This could reflect the quality of services in more

advanced states, where are more sufficiently internationalised.

The correlation of GDP per head levels with high technology exports as a percentage of

exports is significant and enhances. The difference of the correlation coefficient is highly

significant, reflecting the capacity of advanced states to export their products of high

technology and the penetration to the markets of the less advanced states.

Normally we would expect this to be reflected to in the correlation of GDP per head

levels with expenditure of R&D, as a share of GDP. But, the opposite appears as a

picture. A possible explanation for this pattern is that while advanced states achieve to

export their products of high technology in the less advanced, the take less care of the

need to achieve product advancements and that, in other words, the European economy

and its production is dangerously “trapped” by its expansion in the less advanced states

that appears at first to be a beneficial tendency for European production.

Table 3a: Correlation coefficients of GDP per head (constant prices) with the rest of the

variables

df=32 Correl. Coeff.

2-tailed sign.

T Standard

deviation

R – square

GRr01 -0.2281* -1.325 2.602664 -0.05203

48

GRr02 -0.5279*** -3.516 2.286699 -0.278678

GRr03 -0.6096*** -4.35 2.658515 -0.371612

GRr04 -0.4582*** -2.916 2.26192 -0.209947

GRr05 -0.3742*** -2.283 2.570302 -0.140026

GRr06 -0.5109*** -3.362 2.474236 -0.261019

GRr07 -0.3395*** -2.042 2.431661 -0.11526

GRr08 -0.2388 -1.391 2.72994 -0.057025

Prodcom01 0.2963** 1.755 1.71e+08 0.087794

Prodcom02 0.2846* 1.679 1.81e+08 0.080997

Prodcom03 0.2631* 1.543 1.86e+08 0.069222

Prodcom04 0.2477* 1.446 1.88e+08 0.061355

Prodcom05 0.2051 1.185 1.98e+08 0.042066

Prodcom06 0.1971 1.137 2.24e+08 0.038848

Prodcom07 0.1791 1.03 2.44e+08 0.032077

Prodcom08 0.1933 1.114 2.57e+08 0.037365

VlFrTrlGDP01 0.1219 0.695 5.357111 0.01486

VlFrTrlGDP02 -0.0718 -0.407 7.462534 -0.005155

VlFrTrlGDP03 -0.0700 -0.397 9.864631 -0.0049

VlFrTrlGDP04 -0.2307* -1.341 15.71791 -0.053222

VlFrTrlGDP05 -0.4101*** -2.544 21.08554 -0.168182

VlFrTrlGDP06 -0.3741*** -2.282 23.3759 -0.139951

VlFrTrlGDP07 -0.3897*** -2.394 25.3045 -0.151866

VlFrTrlGDP08 -0.3374** -2.028 23.68023 -0.113839

VlPsTrlGDP01 0.3153** 1.879 1.974421 0.099414

VlPsTrlGDP02 0.3325** 2.013 3.731677 0.110556

VlPsTrlGDP03 0.4307*** 2.7 4.873925 0.185502

VlPsTrlGDP04 0.4083*** 2.53 6.015109 0.166709

VlPsTrlGDP05 0.3176** 1.895 7.089047 0.10087

VlPsTrlGDP06 0.2527* 1.477 8.139106 0.063857

VlPsTrlGDP07 0.1912 1.102 9.490892 0.036557

VlPsTrlGDP08 0.1777 1.021 10.66328 0.031577

InOutFDI02 0.6043*** 4.29 108.2556 0.365178

InOutFDI03 0.6231*** 4.507 65.62105 0.388254

InOutFDI04 0.6168*** 4.433 48.20872 0.380442

InOutFDI05 0.6450*** 4.775 64.46886 0.416025

InOutFDI06 0.6644*** 5.029 57.24978 0.441427

InOutFDI07 0.7072*** 5.658 89.65543 0.500132

InOutFDI08 0.7191*** 5.854 40.85154 0.517105

outFDI02 0.6288*** 4.575 115.761 0.395389

outFDI03 0.6526*** 4.872 70.76493 0.425887

outFDI04 0.6680*** 5.078 50.94433 0.446224

outFDI05 0.6959*** 5.482 68.39839 0.484277

outFDI06 0.7183*** 5.84 55.35354 0.515955

outFDI07 0.7394*** 6.213 107.098 0.546712

outFDI08 0.7720*** 6.871 47.04136 0.595984

inFDI02 0.6119*** 4.376 103.2987 0.374422

inFDI03 0.6278*** 4.563 62.06766 0.394133

inFDI04 0.5909*** 4.143 46.71131 0.349163

inFDI05 0.6214*** 4.487 62.22153 0.386138

inFDI06 0.6421*** 4.738 60.57909 0.412292

inFDI07 0.7038*** 5.604 74.65783 0.495334

inFDI08 0.6695*** 5.099 35.91137 0.44823

fGFC01 0.9842*** 31.444 2715.151 0.96865

49

fGFC02 0.9809*** 28.527 2690.084 0.962165

fGFC03 0.9788*** 27.033 2670.678 0.958049

fGFC04 0.9775*** 26.215 2766.413 0.955506

fGFC05 0.9643*** 20.599 3042.092 0.929874

fGFC06 0.9460*** 16.508 3208.038 0.894916

fGFC07 0.9745*** 24.567 3332.782 0.94965

fGFC08 0.9884*** 36.815 3107.483 0.976935

CnFC01 0.9673*** 21.574 .0019673 0.935669

CnFC02 0.9596*** 19.293 .0019629 0.920832

CnFC03 0.9497*** 17.155 .0018974 0.90193

CnFC04 0.9554*** 18.301 .0019228 0.912789

CnFC05 0.9514*** 17.476 .0019481 0.905162

CnFC06 0.9488*** 16.991 .0019908 0.900221

CnFC07 0.9458*** 16.475 .0020496 0.894538

CnFC08 0.9541*** 18.021 .0021478 0.910307

HTExp_TExp01 -0.1293 -0.738 12.77679 -0.016718

HTExp_TExp02 0.3610*** 2.19 12.0064 0.130321

HTExp_TExp03 0.3696*** 2.25 11.49399 0.136604

HTExp_TExp04 0.3477*** 2.098 11.15782 0.120895

HTExp_TExp05 0.4070*** 2.521 11.34108 0.165649

HTExp_TExp06 0.4026*** 2.488 11.68472 0.162087

GDERDshGDP01 0.7418*** 6.257 0.8050052 0.550267

GDERDshGDP02 0.7404*** 6.231 0.8169041 0.548192

GDERDshGDP03 0.7662*** 6.745 0.836396 0.587062

GDERDshGDP04 0.7491*** 6.397 0.8171285 0.561151

GDERDshGDP05 0.7013*** 5.565 0.8111644 0.491822

GDERDshGDP06 0.6754*** 5.181 0.7990605 0.456165

GDERDshGDP07 0.6995*** 5.537 0.797811 0.4893

GDERDshGDP08 0.6724*** 5.139 0.854031 0.452122

ntblgd0c01 0.6108*** 4.364 2.484681 0.373077

ntblgd0c02 0.5982*** 4.223 2.471229 0.357843

ntblgd0c03 0.6247*** 4.526 2.262051 0.39025

ntblgd0c04 0.6189*** 4.457 2.27777 0.383037

ntblgd0c05 0.6655*** 5.044 2.475586 0.44289

ntblgd0c06 0.6769*** 5.202 2.675999 0.458194

ntblgd0c07 0.6461*** 4.789 2.524526 0.417445

ntblgd0c08 0.6569*** 4.929 3.082252 0.431518

expgd0c01 0.7940*** 7.388 5.328652 0.630436

expgd0c02 0.7925*** 7.351 5.12906 0.628056

expgd0c03 0.8204*** 8.116 4.597694 0.673056

expgd0c04 0.8207*** 8.125 4.660032 0.673548

expgd0c05 0.8461*** 8.979 5.015632 0.715885

expgd0c06 0.8521*** 9.21 5.375475 0.726074

expgd0c07 0.8262*** 8.296 5.390584 0.682606

expgd0c08 0.8450*** 8.939 5.67624 0.714025

impgd0c01 0.7891*** 7.267 3.484181 0.622679

impgd0c02 0.8065*** 7.716 3.252974 0.650442

impgd0c03 0.8247*** 8.249 2.906905 0.68013

impgd0c04 0.8191*** 8.077 2.990137 0.670925

impgd0c05 0.8173*** 8.024 3.23383 0.667979

impgd0c06 0.8041*** 7.651 3.514757 0.646577

impgd0c07 0.7886*** 7.255 3.659318 0.62189

impgd0c08 0.7672*** 6.766 3.713653 0.588596

50

ntblsr0c01 -0.1749 -1.005 1.100063 -0.03059

ntblsr0c02 -0.1699 -0.975 1.161698 -0.028866

ntblsr0c03 -0.1550 -0.888 1.00521 -0.024025

ntblsr0c04 -0.1111 -0.632 .9520762 -0.012343

ntblsr0c05 -0.1332 -0.76 .9491056 -0.017742

ntblsr0c06 -0.0598 -0.339 .9214788 -0.003576

ntblsr0c07 0.0280 0.158 .8995766 0.000784

ntblsr0c08 -0.0041 -0.023 1.143306 -1.68E-05

expsr0c01 0.6994*** 5.536 1.820349 0.48916

expsr0c02 0.6710*** 5.119 1.95598 0.450241

expsr0c03 0.6680*** 5.078 2.045479 0.446224

expsr0c04 0.6727*** 5.143 2.161508 0.452525

expsr0c05 0.6869*** 5.347 2.340881 0.471832

expsr0c06 0.6729*** 5.146 2.620337 0.452794

expsr0c07 0.6534*** 4.883 2.891944 0.426932

expsr0c08 0.6246*** 4.524 2.982941 0.390125

impsr0c01 0.6688*** 5.089 2.144739 0.447293

impsr0c02 0.6694*** 5.097 2.200198 0.448096

impsr0c03 0.6651*** 5.038 2.230315 0.442358

impsr0c04 0.6626*** 5.004 2.300104 0.439039

impsr0c05 0.6898*** 5.39 2.45074 0.475824

impsr0c06 0.6808*** 5.258 2.611548 0.463489

impsr0c07 0.6826*** 5.284 2.683543 0.465943

impsr0c08 0.6582*** 4.567 2.77072 0.433227

* 0.2 ≥ p ≥ 0.1, ** p ≥ 0.05, *** p ≥ 0.01

Table 3b: Difference of correlation coefficients for GDP per head (constant prices) Variable A Variable B z-score

2-tailed sign.

GRr01 GRr08 0.04

Prodcom01 Prodcom08 0.43

VlFrTrlGDP01 VlFrTrlGDP08 1.86**

VlFrTrlGDP01 VlFrTrlGDP06 2.03***

VlPsTrlGDP01 VlPsTrlGDP08 0.58

InOutFDI02 InOutFDI08 -0.81

outFDI02 outFDI08 -1.13

inFDI02 inFDI08 -0.39

fGFC01 fGFC08 -0.61

CnFC01 CnFC08 0.68

HTExp_TExp01 HTExp_TExp06 -2.19***

GDERDshGDP01 GDERDshGDP08 0.55

ntblgd0c01 ntblgd0c08 -0.3

ntblsr0c01 ntblsr0c08 -0.68

expgd0c01 expgd0c08 -0.62

expsr0c01 expsr0c08 0.53

impgd0c01 impgd0c08 0.22

impsr0c01 impsr0c08 0.07

* 0.2 ≥ p ≥ 0.1, ** p ≥ 0.05, *** p ≥ 0.01

51

Overall, it appears from Tables 1b and 3b (for the change in correlation coefficients with

distance and GDP per head) that only for a very limited number of variables there is a

significant change in correlation coefficients over the study period. This indicates the

limited effects of policies in operation across the whole space studied (34 states included)

and the need for their re-direction. Though significance appears across in many

correlations, indicating the correlation of variables with distance and growth levels, the

new value added produced (gross fixed capital formation, GFC) is very strongly

correlated with growth levels (GDP per head) and similarly is consumption (CFC).

Evidence is provided on the significant change of correlations with growth rates.

9. Epilogue

The creation of the EU was an effort to expand the economic horizon of European states,

by bringing them together and increasing their interaction and the level of competition.

On the historical bases provided by nation-states, which have taken centuries to be

formed and provide a substantial environment as a shell that economises, supports and

sustains wealth, the EU is now under the process of laying down substantial new

foundations through its policies for economic, monetary and political unification, with an

explicitly expressed target to act to the common European benefit.

The present paper has assessed such efforts for a recent period that was associated with

the early steps of monetary unification (2001-2008) by launching a new methodology that

was based on testing the correlation of numerous state-level variables with distance from

Brussels, growth levels and growth rates, for 34 European states. Significant evidence

was provided that the EU strengthens its position. But, as opposed to other studies and

the ambiguity of other evidence, the present work fully rejected the convergence

hypothesis. Strengthening EU capital formation coincides with large gaps between more

and less advanced states and between central and peripheral. A tendency to sustain and

expand a pre-existing dualism and a two-sector European economy between the more

advanced and central states is traced. It appears that EU regional and cohesion policies

have not delivered substantial growth rates in EU peripheral and less advanced states,

52

enough to reduce the intensity of growth gaps. Under the present conditions, it must be

made crystal clear that an extended time period will be needed before reaching some

apparent levels of convergence in Europe, at least in GDP per head levels, creating

doubts on how exactly EU politics consider the prospect of future enlargements.

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61

11. APPENDICES

Appendix A

Table 1: The variables in the study (names, units, explanation or other useful comments) Variable name Variable Units Comments

gdpph01c GDP per head, 2001 Constant 00 GDP per head Index

gdpph02c GDP per head, 2002 Constant 00

gdpph03c GDP per head, 2003 Constant 00

gdpph04c GDP per head, 2004 Constant 00

gdpph05c GDP per head, 2005 Constant 00

gdpph06c GDP per head, 2006 Constant 00

gdpph07c GDP per head, 2007 Constant 00

gdpph08c GDP per head, 2008 Constant 00

InOutFDI02 Market integration – FDI intensity, 2002 Market integration

index, average value of

inward and outward FDI

flows divided by GDP

(in %)

InOutFDI03 Market integration – FDI intensity, 2003

InOutFDI04 Market integration – FDI intensity, 2004

InOutFDI05 Market integration – FDI intensity, 2005

InOutFDI06 Market integration – FDI intensity, 2006

InOutFDI07 Market integration – FDI intensity, 2007

InOutFDI08 Market integration – FDI intensity, 2008

outFDI02 Outward F.D.I., flows in % of 2002 GDP Outward FDI index,

exporting capacity outFDI03 Outward F.D.I., flows in % of 2003 GDP

outFDI04 Outward F.D.I., flows in % of 2004 GDP

outFDI05 Outward F.D.I., flows in % of 2005 GDP

outFDI06 Outward F.D.I., flows in % of 2006 GDP

outFDI07 Outward F.D.I., flows in % of 2007 GDP

outFDI08 Outward F.D.I., flows in % of 2008 GDP

inFDI02 Inward F.D.I., from the rest of the world,

flows in % of 2002 GDP

Inward FDI index

inFDI03 Inward F.D.I. from the rest of the world,

flows in % of 2003 GDP

inFDI04 Inward F.D.I. from the rest of the world,

flows in % of 2004 GDP

inFDI05 Inward F.D.I. from the rest of the world,

flows in % of 2005 GDP

inFDI06 Inward F.D.I. from the rest of the world,

flows in % of 2006 GDP

inFDI07 Inward F.D.I. from the rest of the world,

flows in % of 2007 GDP

inFDI08 Inward F.D.I. from the rest of the world,

flows in % of 2008 GDP

nblgd00 Net balance of goods, 2000 Constant 00 Net Balance of goods

index nblgd0c01 Net balance of goods, 2001 Constant 00

nblgd0c02 Net balance of goods, 2002 Constant 00

nblgd0c03 Net balance of goods, 2003 Constant 00

nblgd0c04 Net balance of goods, 2004 Constant 00

nblgd0c05 Net balance of goods, 2005 Constant 00

nblgd0c06 Net balance of goods, 2006 Constant 00

nblgd0c07 Net balance of goods, 2007 Constant 00

nblgd0c08 Net balance of goods, 2008 Constant 00

ntblsr00 Net balance of services, 2000 Constant 00 Net Balance of Services

index ntblsr0c01 Net balance of services, 2001 Constant 00

62

ntblsr0c02 Net balance of services, 2002 Constant 00

ntblsr0c03 Net balance of services, 2003 Constant 00

ntblsr0c04 Net balance of services, 2004 Constant 00

ntblsr0c05 Net balance of services, 2005 Constant 00

ntblsr0c06 Net balance of services, 2006 Constant 00

ntblsr0c07 Net balance of services, 2007 Constant 00

ntblsr0c08 Net balance of services, 2008 Constant 00

expgd00 Export of goods, 2000 Constant 00 Export of Goods index

expgd0c01 Export of goods, 2001 Constant 00

expgd0c02 Export of goods, 2002 Constant 00

expgd0c03 Export of goods, 2003 Constant 00

expgd0c04 Export of goods, 2004 Constant 00

expgd0c05 Export of goods, 2005 Constant 00

expgd0c06 Export of goods, 2006 Constant 00

expgd0c07 Export of goods, 2007 Constant 00

expgd0c08 Export of goods, 2008 Constant 00

expsr00 Export of Services, 2000 Constant 00 Export of Services index

expsr0c01 Export of Services, 2001 Constant 00

expsr0c02 Export of Services, 2002 Constant 00

expsr0c03 Export of Services, 2003 Constant 00

expsr0c04 Export of Services, 2004 Constant 00

expsr0c05 Export of Services, 2005 Constant 00

expsr0c06 Export of Services, 2006 Constant 00

expsr0c07 Export of Services, 2007 Constant 00

expsr0c08 Export of Services, 2008 Constant 00

impgd00 Import of Goods, 2000 Constant 00 Import of Goods index

impgd0c01 Import of Goods, 2001 Constant 00

impgd0c02 Import of Goods, 2002 Constant 00

impgd0c03 Import of Goods, 2003 Constant 00

impgd0c04 Import of Goods, 2004 Constant 00

impgd0c05 Import of Goods, 2005 Constant 00

impgd0c06 Import of Goods, 2006 Constant 00

impgd0c07 Import of Goods, 2007 Constant 00

impgd0c08 Import of Goods, 2008 Constant 00

impsr00 Import of Services, 2000 Constant 00 Import of Services index

impsr0c01 Import of Services, 2001 Constant 00

impsr0c02 Import of Services, 2002 Constant 00

impsr0c03 Import of Services, 2003 Constant 00

impsr0c04 Import of Services, 2004 Constant 00

impsr0c05 Import of Services, 2005 Constant 00

impsr0c06 Import of Services, 2006 Constant 00

impsr0c07 Import of Services, 2007 Constant 00

impsr0c08 Import of Services, 2008 Constant 00

prodcom01 Value of the production of manufactured

goods, PRODCOM (NACE Rev 2), 2001

Manufacturing

production indicator,

Added sum of

manufacturing

production for every

manufacturing activity,

confidential information

is not included in

official EU source

prodcom02 Value of the production of manufactured

goods, PRODCOM (NACE Rev 2) 2002

prodcom03 Value of the production of manufactured

goods, PRODCOM (NACE Rev 2) 2003

prodcom04 Value of the production of manufactured

goods, PRODCOM (NACE Rev 2) 2004

prodcom05 Value of the production of manufactured

goods, PRODCOM (NACE Rev 2) 2005

prodcom06 Value of the production of manufactured

63

goods, PRODCOM (NACE Rev 2) 2006

prodcom07 Value of the production of manufactured

goods, PRODCOM (NACE Rev 2) 2007

prodcom08 Value of the production of manufactured

goods, PRODCOM (NACE Rev 2) 2008

VlPsTrlGDP01 Volume of Passenger Transport

relative to GDP, 2001

Index of Passenger

Transport

VlPsTrlGDP02 Volume of Passenger Transport

relative to GDP, 2002

VlPsTrlGDP03 Volume of Passenger Transport

relative to GDP, 2003

VlPsTrlGDP04 Volume of Passenger Transport

relative to GDP, 2004

VlPsTrlGDP05 Volume of Passenger Transport

relative to GDP, 2005

VlPsTrlGDP06 Volume of Passenger Transport

relative to GDP, 2006

VlPsTrlGDP07 Volume of Passenger Transport

relative to GDP, 2007

VlPsTrlGDP08 Volume of Passenger Transport

relative to GDP, 2008

VlFrTrlGDp01 Volume of Freight Transport

relative to GDP, 2001

Index of Volume in

Transport

VlFrTrlGDp02 Volume of Freight Transport

relative to GDP, 2002

VlFrTrlGDp03 Volume of Freight Transport

relative to GDP, 2003

VlFrTrlGDp04 Volume of Freight Transport

relative to GDP, 2004

VlFrTrlGDp05 Volume of Freight Transport

relative to GDP, 2005

VlFrTrlGDp06 Volume of Freight Transport

relative to GDP, 2006

VlFrTrlGDp07 Volume of Freight Transport

relative to GDP, 2007

VlFrTrlGDp08 Volume of Freight Transport

relative to GDP, 2008

fGFC01 Formation of Gross Fixed Capital, 2001

fGFC02 Formation of Gross Fixed Capital, 2002

fGFC03 Formation of Gross Fixed Capital, 2003

fGFC04 Formation of Gross Fixed Capital, 2004

fGFC05 Formation of Gross Fixed Capital, 2005

fGFC06 Formation of Gross Fixed Capital, 2006

fGFC07 Formation of Gross Fixed Capital, 2007

fGFC08 Formation of Gross Fixed Capital, 2008

CnFC01 Consumption of Fixed Capital, 2001

CnFC02 Consumption of Fixed Capital, 2002

CnFC03 Consumption of Fixed Capital, 2003

CnFC04 Consumption of Fixed Capital, 2004

CnFC05 Consumption of Fixed Capital, 2005

CnFC06 Consumption of Fixed Capital, 2006

CnFC07 Consumption of Fixed Capital, 2007

CnFC08 Consumption of Fixed Capital, 2008

LC_ind0c01 Labour Costs in industry, 2001 Labour Cost Index

64

LC_ind0c02 Labour Costs in industry, 2002 constant 00

LC_ind0c03 Labour Costs in industry, 2003 constant 00

LC_ind0c04 Labour Costs in industry, 2004 constant 00

LC_ind0c05 Labour Costs in industry, 2005 constant 00

LC_ind0c06 Labour Costs in industry, 2006 constant 00

LC_ind0c07 Labour Costs in industry, 2007 constant 00

LC_ind0c08 Labour Costs in industry, 2008 constant 00

HTExp_TExp00 High Tech Exports as a proportion of

total exports, 2000

Technology Exports

Index

HTExp_TExp01 High Tech Exports as a proportion of

total exports, 2001

HTExp_TExp02 High Tech Exports as a proportion of

total exports, 2002

HTExp_TExp03 High Tech Exports as a proportion of

total exports, 2003

HTExp_TExp04 High Tech Exports as a proportion of

total exports, 2004

HTExp_TExp05 High Tech Exports as a proportion of

total exports, 2005

HTExp_TExp06 High Tech Exports as a proportion of

total exports, 2006

GDERDshGDP00 Gross Domestic Expenditure in R&D as

percentage of GDP 2000

R&D index

GDERDshGDP01 Gross Domestic Expenditure in R&D as

percentage of GDP 2001

GDERDshGDP02 Gross Domestic Expenditure in R&D as

percentage of GDP 2002

GDERDshGDP03 Gross Domestic Expenditure in R&D as

percentage of GDP 2003

GDERDshGDP04 Gross Domestic Expenditure in R&D as

percentage of GDP 2004

GDERDshGDP05 Gross Domestic Expenditure in R&D as

percentage of GDP 2005

GDERDshGDP06 Gross Domestic Expenditure in R&D as

percentage of GDP 2006

GDERDshGDP07 Gross Domestic Expenditure in R&D as

percentage of GDP 2007

GDERDshGDP08 Gross Domestic Expenditure in R&D as

percentage of GDP 2008

GRr00 Growth Rate, 2000 Growth Rate index

GRr01 Growth Rate, 2001

GRr02 Growth Rate, 2002

GRr03 Growth Rate, 2003

GRr04 Growth Rate, 2004

GRr05 Growth Rate, 2005

GRr06 Growth Rate, 2006

GRr07 Growth Rate, 2007

GRr08 Growth Rate, 2008

65

Table 2: The 34 countries included in the study

Country Status Country Status Country Status Country Status

Belgium EU Italy EU Portugal EU Iceland

EU

candidate

Bulgaria EU Cyprus EU Romania EU Liechtenstein Non – EU

Czech

Republic

EU Latvia EU Slovenia EU Norway Non – EU

Denmark EU Lithuania EU Slovakia EU Switzerland Non – EU

Germany EU Luxembourg EU Finland EU Croatia EU

candidate

Estonia EU Hungary EU Sweden EU FYROM EU

candidate

Ireland EU Malta EU United

Kingdom

EU Turkey EU

candidate

Greece EU Netherlands EU

Spain EU Austria EU

France EU Poland EU

Appendix B

Appendix B2: Private Saving and Investment (% GDP)

10.0

12.5

15.0

17.5

20.0

22.5

25.0

92 94 96 98 00 02 04 06 08 10

GREECE

10.0

12.5

15.0

17.5

20.0

22.5

25.0

92 94 96 98 00 02 04 06 08 10

PORTUGAL

14

16

18

20

22

24

26

28

92 94 96 98 00 02 04 06 08 10

SPAIN

16

18

20

22

24

26

28

92 94 96 98 00 02 04 06 08 10

ITALY

14

15

16

17

18

19

20

21

92 94 96 98 00 02 04 06 08 10

FRANCE

0

5

10

15

20

25

30

92 94 96 98 00 02 04 06 08 10

CYPRUS

16

18

20

22

24

26

92 94 96 98 00 02 04 06 08 10

Private Investment (% GDP)

Private Saving (% GDP)

SLOVENIA

Source: Kosteletou, 2012, data from European Commission, Economic and Financial

Affairs.

66

Appendix B2: Net Private and Public Saving (% GDP)

-20

-15

-10

-5

0

5

10

92 94 96 98 00 02 04 06 08 10

GREECE

-10

-8

-6

-4

-2

0

2

4

92 94 96 98 00 02 04 06 08 10

PORTUGAL

-16

-12

-8

-4

0

4

8

92 94 96 98 00 02 04 06 08 10

SPAIN

-12

-8

-4

0

4

8

12

92 94 96 98 00 02 04 06 08 10

ITALY

-8

-6

-4

-2

0

2

4

6

92 94 96 98 00 02 04 06 08 10

FRANCE

-20

-15

-10

-5

0

5

10

92 94 96 98 00 02 04 06 08 10

CYPRUS

-6

-4

-2

0

2

4

6

92 94 96 98 00 02 04 06 08 10

Net public Saving (Saving - Investment) (% GDP)

Net Private Saving (Saving - Investment) (% GDP)

SLOVENIA

Source: Kosteletou, 2012, data from European Commission, Economic and Financial

Affairs.

67

Appendix C

GDPph_c 0

.00

0.2

50

.50

0.7

51

.00

No

rma

l F[(

gd

pp

h0

1c-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00.7

51

.00

No

rmal F

[(g

dp

ph0

2c-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

gdpp

h03c

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(g

dp

ph

04

c-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

gdpp

h05c

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(gdpph06c-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

gdpp

h07c

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

gd

pp

h0

8c-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

68

GRr

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

GR

r00

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(G

Rr0

1-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

GR

r02-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

GR

r03

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

GR

r04-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

GR

r05

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

GR

r06-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

GR

r07

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

GR

r08-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

69

Prodcom

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

prod

com

01-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(p

rod

com

02

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

prod

com

03-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

pro

dco

m0

4-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

pro

dco

m0

5-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(p

rod

com

06

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

pro

dco

m0

7-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(p

rod

com

08

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

70

VIFrTrGDP

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

VlF

rTrlG

Dp0

1-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

VlF

rTrlG

Dp0

2-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

VlF

rTrlG

Dp0

3-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

VlF

rTrlG

Dp0

4-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

VlF

rTrlG

Dp0

5-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

VlF

rTrlG

Dp0

6-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(V

lFrT

rlG

Dp07-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(V

lFrT

rlG

Dp08-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

71

VIPsTrGDP

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

VlP

sTrlG

DP

01

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(V

lPsT

rlG

DP

02-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(V

lPsT

rlG

DP

03

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(V

lPsT

rlG

DP

04-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(V

lPsT

rlG

DP

05-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(V

lPsT

rlG

DP

06-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

VlP

sTrlG

DP

07

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

VlP

sTrlG

DP

08-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

72

InOutFDI

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

InO

utFD

I02-

m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

InO

utF

DI0

3-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(I

nOut

FDI0

4-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.

000.

250.

500.

751.

00

Nor

mal

F[(

InO

utFD

I05-

m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

InO

utF

DI0

6-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

InO

utF

DI0

7-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(In

Ou

tFD

I08

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

73

OutFDI

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

outF

DI0

2-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

outF

DI0

3-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

ou

tFD

I04

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

ou

tFD

I05

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

outF

DI0

6-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

outF

DI0

7-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

outF

DI0

8-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

74

inFDI

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

inF

DI0

2-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

inF

DI0

3-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

inFD

I04-

m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

inFD

I05-

m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

inFD

I06-

m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

inFD

I07-

m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

inFD

I08-

m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

75

fGFC

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

fGF

C01

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

fGF

C02

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

fGF

C03

-m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

fGF

C04

-m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

fGF

C05

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

fGF

C06

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(fG

FC

07-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(fG

FC

08-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

76

CnFC

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

CnF

C01

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

CnF

C02

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

CnF

C03

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(C

nF

C04-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

Cn

FC

05

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(C

nF

C0

6-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

Cn

FC

07

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

Cn

FC

08

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

77

LC_ind0c

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

LC_i

nd0c

01-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

LC

_in

d0

c02

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

LC_i

nd0c

03-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

LC_i

nd0c

04-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

LC

_in

d0

c05

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

LC

_in

d0

c06

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

LC_i

nd0c

07-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(LC

_in

d0c0

8-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

78

HTexp_Texp

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(H

TExp

_TE

xp00

-m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(H

TExp

_TE

xp01

-m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(H

TExp

_TE

xp02

-m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(H

TExp

_TE

xp03

-m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

HT

Exp

_TE

xp04

-m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(H

TExp

_TE

xp05

-m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

HT

Exp

_TE

xp06

-m)/s

]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

79

GDERDshGDP

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

GD

ER

Dsh

GD

P0

0-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(G

DE

RD

sh

GD

P0

1-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50

.50

0.7

51

.00

No

rma

l F[(

GD

ER

Dsh

GD

P0

2-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50

.50

0.7

51

.00

No

rma

l F

[(G

DE

RD

shG

DP

03-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

GD

ER

Dsh

GD

P04

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

GD

ER

Dsh

GD

P0

5-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

GD

ER

Dsh

GD

P06

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

GD

ER

Dsh

GD

P0

7-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

GD

ER

Dsh

GD

P08

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

80

Ntblgd

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

nb

lgd

00

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

nblg

d0c0

1-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(nblg

d0c0

2-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

nblg

d0c0

3-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

nb

lgd

0c0

4-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

nb

lgd

0c0

5-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

nblg

d0c0

6-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

nblg

d0c0

7-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(nblg

d0c0

8-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

81

expgd0c

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

exp

gd

00

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(exp

gd0c0

1-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50

.50

0.7

51

.00

No

rma

l F

[(e

xpg

d0c0

2-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(exp

gd0c03-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

exp

gd

0c0

4-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(exp

gd0c0

5-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rmal F

[(exp

gd

0c0

6-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rmal F

[(exp

gd

0c0

7-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

exp

gd

0c0

8-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

82

impgd0c

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

impg

d00-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(im

pgd0c0

1-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

impg

d0c0

2-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

imp

gd

0c0

3-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

impg

d0c0

4-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

impg

d0c0

5-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

impg

d0c0

6-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(im

pgd0c0

7-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(im

pgd0c0

8-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

83

ntblsr0c

0.0

00.2

50.5

00.7

51.0

0

Norm

al F

[(ntb

lsr0

0-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

Norm

al F

[(n

tbls

r0c0

1-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

ntbl

sr0c

02-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

ntb

lsr0

c03

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

ntbl

sr0c

04-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

ntbl

sr0c

05-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

ntb

lsr0

c06

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

ntb

lsr0

c07

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(n

tbls

r0c0

8-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

84

expsr0c

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

exp

sr0

0-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

exp

sr0

c01

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

exp

sr0

c02

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

exp

sr0

c03

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F

[(e

xpsr0

c04

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

exp

sr0

c05

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

exp

sr0

c06

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

exps

r0c0

7-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

exps

r0c0

8-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

85

impsr0c 0.

000.

250.

500.

751.

00

Nor

mal

F[(

imps

r00-

m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

imps

r0c0

1-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

imps

r0c0

2-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.0

00

.25

0.5

00

.75

1.0

0

No

rma

l F[(

imp

sr0

c03

-m)/

s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

imps

r0c0

4-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

imps

r0c0

5-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

imps

r0c0

6-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

imps

r0c0

7-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

0.00

0.25

0.50

0.75

1.00

Nor

mal

F[(

imps

r0c0

8-m

)/s]

0.00 0.25 0.50 0.75 1.00Empirical P[i] = i/(N+1)

86

Appendix D: Basic maps, selected variables, selected years and change

87

88

89

90

91